
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

import warnings
warnings.filterwarnings("ignore")

%matplotlib inline
import seaborn as sns
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
from sklearn import tree

# To build linear model for statistical analysis and prediction
import statsmodels.stats.api as sms
from statsmodels.stats.outliers_influence import variance_inflation_factor
import statsmodels.api as sm
from statsmodels.tools.tools import add_constant

# To tune different models
from sklearn.model_selection import GridSearchCV


# To get diferent metric scores
from sklearn.metrics import (
    f1_score,
    accuracy_score,
    recall_score,
    precision_score,
    confusion_matrix,
    roc_auc_score,
    plot_confusion_matrix,
    precision_recall_curve,
    roc_curve,
    make_scorer,
)


# this will help in making the Python code more structured automatically (good coding practice)
%load_ext nb_black


# loading the dataset
data = pd.read_csv("INNHotelsGroup.csv")


# checking the shape of the data

data.shape

print(f"The data contains {data.shape[0]} rows")  # f-string
print(f"The data contains {data.shape[1]} columns")  # f-string

The data contains 36275 rows
The data contains 19 columns


# let's view a sample of the data
data.sample(15, random_state=23)


# creating a copy of the data so that original data remains unchanged
df = data.copy()


# checking for duplicate values in the data
df.duplicated().sum()

0


# checking column datatypes and number of non-null values
df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 36275 entries, 0 to 36274
Data columns (total 19 columns):
 #   Column                                Non-Null Count  Dtype  
---  ------                                --------------  -----  
 0   Booking_ID                            36275 non-null  object 
 1   no_of_adults                          36275 non-null  int64  
 2   no_of_children                        36275 non-null  int64  
 3   no_of_weekend_nights                  36275 non-null  int64  
 4   no_of_week_nights                     36275 non-null  int64  
 5   type_of_meal_plan                     36275 non-null  object 
 6   required_car_parking_space            36275 non-null  int64  
 7   room_type_reserved                    36275 non-null  object 
 8   lead_time                             36275 non-null  int64  
 9   arrival_year                          36275 non-null  int64  
 10  arrival_month                         36275 non-null  int64  
 11  arrival_date                          36275 non-null  int64  
 12  market_segment_type                   36275 non-null  object 
 13  repeated_guest                        36275 non-null  int64  
 14  no_of_previous_cancellations          36275 non-null  int64  
 15  no_of_previous_bookings_not_canceled  36275 non-null  int64  
 16  avg_price_per_room                    36275 non-null  float64
 17  no_of_special_requests                36275 non-null  int64  
 18  booking_status                        36275 non-null  object 
dtypes: float64(1), int64(13), object(5)
memory usage: 5.3+ MB


# checking for missing values in the data.
df.isnull().sum()

Booking_ID                              0
no_of_adults                            0
no_of_children                          0
no_of_weekend_nights                    0
no_of_week_nights                       0
type_of_meal_plan                       0
required_car_parking_space              0
room_type_reserved                      0
lead_time                               0
arrival_year                            0
arrival_month                           0
arrival_date                            0
market_segment_type                     0
repeated_guest                          0
no_of_previous_cancellations            0
no_of_previous_bookings_not_canceled    0
avg_price_per_room                      0
no_of_special_requests                  0
booking_status                          0
dtype: int64


# Statistical summary of the data
df.describe(include="all").T


df["booking_status"].value_counts()

Not_Canceled    24390
Canceled        11885
Name: booking_status, dtype: int64


for feature in df.columns:  # Loop through all columns in the dataframe
    if df[feature].dtype == "object":  # Only apply for columns with object strings
        df[feature] = pd.Categorical(df[feature])  # Replace object with categorical
df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 36275 entries, 0 to 36274
Data columns (total 19 columns):
 #   Column                                Non-Null Count  Dtype   
---  ------                                --------------  -----   
 0   Booking_ID                            36275 non-null  category
 1   no_of_adults                          36275 non-null  int64   
 2   no_of_children                        36275 non-null  int64   
 3   no_of_weekend_nights                  36275 non-null  int64   
 4   no_of_week_nights                     36275 non-null  int64   
 5   type_of_meal_plan                     36275 non-null  category
 6   required_car_parking_space            36275 non-null  int64   
 7   room_type_reserved                    36275 non-null  category
 8   lead_time                             36275 non-null  int64   
 9   arrival_year                          36275 non-null  int64   
 10  arrival_month                         36275 non-null  int64   
 11  arrival_date                          36275 non-null  int64   
 12  market_segment_type                   36275 non-null  category
 13  repeated_guest                        36275 non-null  int64   
 14  no_of_previous_cancellations          36275 non-null  int64   
 15  no_of_previous_bookings_not_canceled  36275 non-null  int64   
 16  avg_price_per_room                    36275 non-null  float64 
 17  no_of_special_requests                36275 non-null  int64   
 18  booking_status                        36275 non-null  category
dtypes: category(5), float64(1), int64(13)
memory usage: 5.4 MB


for feature in df.columns:  # Loop through all columns in the dataframe
    if df[feature].dtype != "int64":  # Only apply for columns with categorical strings
        print(df[feature].value_counts())

INN00001    1
INN24187    1
INN24181    1
INN24182    1
INN24183    1
           ..
INN12086    1
INN12085    1
INN12084    1
INN12083    1
INN36275    1
Name: Booking_ID, Length: 36275, dtype: int64
Meal Plan 1     27835
Not Selected     5130
Meal Plan 2      3305
Meal Plan 3         5
Name: type_of_meal_plan, dtype: int64
Room_Type 1    28130
Room_Type 4     6057
Room_Type 6      966
Room_Type 2      692
Room_Type 5      265
Room_Type 7      158
Room_Type 3        7
Name: room_type_reserved, dtype: int64
Online           23214
Offline          10528
Corporate         2017
Complementary      391
Aviation           125
Name: market_segment_type, dtype: int64
65.00     848
75.00     826
90.00     703
95.00     669
115.00    662
         ... 
139.88      1
82.59       1
126.69      1
108.35      1
178.33      1
Name: avg_price_per_room, Length: 3930, dtype: int64
Not_Canceled    24390
Canceled        11885
Name: booking_status, dtype: int64


# function to plot a boxplot and a histogram along the same scale.


def histogram_boxplot(data, feature, figsize=(12, 7), kde=False, bins=None):
    """
    Boxplot and histogram combined

    data: dataframe
    feature: dataframe column
    figsize: size of figure (default (12,7))
    kde: whether to the show density curve (default False)
    bins: number of bins for histogram (default None)
    """
    f2, (ax_box2, ax_hist2) = plt.subplots(
        nrows=2,  # Number of rows of the subplot grid= 2
        sharex=True,  # x-axis will be shared among all subplots
        gridspec_kw={"height_ratios": (0.25, 0.75)},
        figsize=figsize,
    )  # creating the 2 subplots
    sns.boxplot(
        data=data, x=feature, ax=ax_box2, showmeans=True, color="violet"
    )  # boxplot will be created and a star will indicate the mean value of the column
    sns.histplot(
        data=data, x=feature, kde=kde, ax=ax_hist2, bins=bins, palette="winter"
    ) if bins else sns.histplot(
        data=data, x=feature, kde=kde, ax=ax_hist2
    )  # For histogram
    ax_hist2.axvline(
        data[feature].mean(), color="green", linestyle="--"
    )  # Add mean to the histogram
    ax_hist2.axvline(
        data[feature].median(), color="black", linestyle="-"
    )  # Add median to the histogram


# function to create labeled barplots


def labeled_barplot(data, feature, perc=False, n=None):
    """
    Barplot with percentage at the top

    data: dataframe
    feature: dataframe column
    perc: whether to display percentages instead of count (default is False)
    n: displays the top n category levels (default is None, i.e., display all levels)
    """

    total = len(data[feature])  # length of the column
    count = data[feature].nunique()
    if n is None:
        plt.figure(figsize=(count + 1, 5))
    else:
        plt.figure(figsize=(n + 1, 5))

    plt.xticks(rotation=90, fontsize=15)
    ax = sns.countplot(
        data=data,
        x=feature,
        palette="Paired",
        order=data[feature].value_counts().index[:n].sort_values(),
    )

    for p in ax.patches:
        if perc == True:
            label = "{:.1f}%".format(
                100 * p.get_height() / total
            )  # percentage of each class of the category
        else:
            label = p.get_height()  # count of each level of the category

        x = p.get_x() + p.get_width() / 2  # width of the plot
        y = p.get_height()  # height of the plot

        ax.annotate(
            label,
            (x, y),
            ha="center",
            va="center",
            size=12,
            xytext=(0, 5),
            textcoords="offset points",
        )  # annotate the percentage

    plt.show()  # show the plot


histogram_boxplot(df, "no_of_adults")


labeled_barplot(df, "no_of_adults")


df.loc[df["no_of_adults"] == 0]


histogram_boxplot(df, "no_of_children")


labeled_barplot(df, "no_of_children")


histogram_boxplot(df, "no_of_weekend_nights")


labeled_barplot(df, "no_of_weekend_nights")


histogram_boxplot(df, "no_of_week_nights")


labeled_barplot(df, "no_of_week_nights")


labeled_barplot(df, "type_of_meal_plan")


histogram_boxplot(df, "required_car_parking_space")


labeled_barplot(df, "required_car_parking_space")


labeled_barplot(df, "room_type_reserved")


histogram_boxplot(df, "lead_time")


histogram_boxplot(df, "arrival_year")


histogram_boxplot(df, "arrival_month")


histogram_boxplot(df, "arrival_date")


labeled_barplot(df, "market_segment_type")


histogram_boxplot(df, "repeated_guest")


labeled_barplot(df, "repeated_guest")


histogram_boxplot(df, "no_of_previous_cancellations")


labeled_barplot(df, "no_of_previous_cancellations")


histogram_boxplot(df, "no_of_previous_bookings_not_canceled")


df["no_of_previous_bookings_not_canceled"].value_counts()

0     35463
1       228
2       112
3        80
4        65
5        60
6        36
7        24
8        23
10       19
9        19
11       15
12       12
14        9
15        8
13        7
16        7
20        6
17        6
18        6
19        6
22        6
21        6
27        3
23        3
24        3
25        3
28        2
30        2
29        2
26        2
48        2
31        2
44        2
32        2
47        1
55        1
33        1
34        1
35        1
36        1
58        1
37        1
57        1
38        1
56        1
39        1
40        1
54        1
41        1
53        1
42        1
52        1
43        1
51        1
50        1
45        1
49        1
46        1
Name: no_of_previous_bookings_not_canceled, dtype: int64


histogram_boxplot(df, "avg_price_per_room")


min_price = df["avg_price_per_room"].min()
max_price = df["avg_price_per_room"].max()

print(f" Minimum price for rent a room per night is {min_price}")
print(f" Maximum price for rent a room per night is {max_price}")

 Minimum price for rent a room per night is 0.0
 Maximum price for rent a room per night is 540.0


histogram_boxplot(df, "no_of_special_requests")


df["no_of_special_requests"].value_counts()

0    19777
1    11373
2     4364
3      675
4       78
5        8
Name: no_of_special_requests, dtype: int64


labeled_barplot(df, "booking_status")


sns.set_style("darkgrid")
df.hist(figsize=(15, 10), bins=12)
plt.show()


### function to plot distributions wrt target


def distribution_plot_wrt_target(data, predictor, target):

    fig, axs = plt.subplots(2, 2, figsize=(12, 10))

    target_uniq = data[target].unique()

    axs[0, 0].set_title("Distribution of target for target=" + str(target_uniq[0]))
    sns.histplot(
        data=data[data[target] == target_uniq[0]],
        x=predictor,
        kde=True,
        ax=axs[0, 0],
        color="teal",
        stat="density",
    )

    axs[0, 1].set_title("Distribution of target for target=" + str(target_uniq[1]))
    sns.histplot(
        data=data[data[target] == target_uniq[1]],
        x=predictor,
        kde=True,
        ax=axs[0, 1],
        color="orange",
        stat="density",
    )

    axs[1, 0].set_title("Boxplot w.r.t target")
    sns.boxplot(data=data, x=target, y=predictor, ax=axs[1, 0], palette="gist_rainbow")

    axs[1, 1].set_title("Boxplot (without outliers) w.r.t target")
    sns.boxplot(
        data=data,
        x=target,
        y=predictor,
        ax=axs[1, 1],
        showfliers=False,
        palette="gist_rainbow",
    )

    plt.tight_layout()
    plt.show()


def stacked_barplot(data, predictor, target):
    """
    Print the category counts and plot a stacked bar chart

    data: dataframe
    predictor: independent variable
    target: target variable
    """
    count = data[predictor].nunique()
    sorter = data[target].value_counts().index[-1]
    tab1 = pd.crosstab(data[predictor], data[target], margins=True).sort_values(
        by=sorter, ascending=False
    )
    print(tab1)
    print("-" * 120)
    tab = pd.crosstab(data[predictor], data[target], normalize="index").sort_values(
        by=sorter, ascending=False
    )
    tab.plot(kind="bar", stacked=True, figsize=(count + 5, 5))
    plt.legend(
        loc="lower left", frameon=False,
    )
    plt.legend(loc="upper left", bbox_to_anchor=(1, 1))
    plt.show()


plt.figure(figsize=(15, 7))
sns.heatmap(df.corr(), annot=True, vmin=-1, vmax=1)
plt.show()


df_pair = df.copy()
df_pair.drop(
    [
        "no_of_adults",
        "no_of_children",
        "no_of_weekend_nights",
        "no_of_week_nights",
        "arrival_date",
        "no_of_special_requests",
        "arrival_date",
        "arrival_year",
        "required_car_parking_space",
    ],
    axis=1,
    inplace=True,
)
sns.pairplot(df_pair, hue="booking_status")
plt.show()


plt.figure(figsize=(12, 6))
sns.barplot(
    data=df, x="market_segment_type", y="avg_price_per_room", hue="booking_status"
)

plt.legend(loc="upper left")
plt.show()


plt.figure(figsize=(12, 6))

sns.countplot(data=df, x="market_segment_type", hue="booking_status")
plt.show()


stacked_barplot(data, "market_segment_type", "booking_status")

booking_status       Canceled  Not_Canceled    All
market_segment_type                               
All                     11885         24390  36275
Online                   8475         14739  23214
Offline                  3153          7375  10528
Corporate                 220          1797   2017
Aviation                   37            88    125
Complementary               0           391    391
------------------------------------------------------------------------------------------------------------------------


plt.figure(figsize=(12, 6))
sns.boxplot(data=data, x="market_segment_type", y="avg_price_per_room")
plt.show()


plt.figure(figsize=(12, 6))

sns.countplot(data=df, x="no_of_children", hue="booking_status")
plt.show()


stacked_barplot(data, "no_of_children", "booking_status")

booking_status  Canceled  Not_Canceled    All
no_of_children                               
All                11885         24390  36275
0                  10882         22695  33577
1                    540          1078   1618
2                    457           601   1058
3                      5            14     19
9                      1             1      2
10                     0             1      1
------------------------------------------------------------------------------------------------------------------------


plt.figure(figsize=(12, 6))

sns.countplot(data=df, x="required_car_parking_space", hue="booking_status")
plt.show()


stacked_barplot(data, "required_car_parking_space", "booking_status")

booking_status              Canceled  Not_Canceled    All
required_car_parking_space                               
All                            11885         24390  36275
0                              11771         23380  35151
1                                114          1010   1124
------------------------------------------------------------------------------------------------------------------------


plt.figure(figsize=(12, 6))

sns.countplot(data=df, x="no_of_special_requests", hue="booking_status")
plt.show()


stacked_barplot(data, "no_of_special_requests", "booking_status")

booking_status          Canceled  Not_Canceled    All
no_of_special_requests                               
All                        11885         24390  36275
0                           8545         11232  19777
1                           2703          8670  11373
2                            637          3727   4364
3                              0           675    675
4                              0            78     78
5                              0             8      8
------------------------------------------------------------------------------------------------------------------------


stacked_barplot(data, "no_of_adults", "booking_status")

booking_status  Canceled  Not_Canceled    All
no_of_adults                                 
All                11885         24390  36275
2                   9119         16989  26108
1                   1856          5839   7695
3                    863          1454   2317
0                     44            95    139
4                      3            13     16
------------------------------------------------------------------------------------------------------------------------


stacked_barplot(data, "repeated_guest", "booking_status")

booking_status  Canceled  Not_Canceled    All
repeated_guest                               
All                11885         24390  36275
0                  11869         23476  35345
1                     16           914    930
------------------------------------------------------------------------------------------------------------------------


stacked_barplot(data, "arrival_month", "booking_status")

booking_status  Canceled  Not_Canceled    All
arrival_month                                
All                11885         24390  36275
10                  1880          3437   5317
9                   1538          3073   4611
8                   1488          2325   3813
7                   1314          1606   2920
6                   1291          1912   3203
4                    995          1741   2736
5                    948          1650   2598
11                   875          2105   2980
3                    700          1658   2358
2                    430          1274   1704
12                   402          2619   3021
1                     24           990   1014
------------------------------------------------------------------------------------------------------------------------


df1 = df.copy()  # Make a copy of the data


df1.isnull().sum()

Booking_ID                              0
no_of_adults                            0
no_of_children                          0
no_of_weekend_nights                    0
no_of_week_nights                       0
type_of_meal_plan                       0
required_car_parking_space              0
room_type_reserved                      0
lead_time                               0
arrival_year                            0
arrival_month                           0
arrival_date                            0
market_segment_type                     0
repeated_guest                          0
no_of_previous_cancellations            0
no_of_previous_bookings_not_canceled    0
avg_price_per_room                      0
no_of_special_requests                  0
booking_status                          0
dtype: int64


df1.drop(
    ["Booking_ID"], axis=1, inplace=True
)  # drop booking_id column as this information


df1.sample(5)


df1.booking_status = df1.booking_status.apply(lambda x: 1 if x == "Canceled" else 0)
df1["booking_status"] = df1["booking_status"].astype(float)


replaceStruct = {
    "type_of_meal_plan": {
        "Meal Plan 1": 1,
        "Meal Plan 2": 2,
        "Meal Plan 3": 3,
        "Not Selected": -1,
    },
}

df1 = df1.replace(replaceStruct)


dummy_col = ["room_type_reserved", "market_segment_type"]
df1 = pd.get_dummies(df1, columns=dummy_col)


df1.loc[df1["lead_time"] <= 30, "lead_time_category"] = 1
df1.loc[df1["lead_time"] > 30, "lead_time_category"] = 2
df1.loc[df1["lead_time"] > 60, "lead_time_category"] = 3
df1.loc[df1["lead_time"] > 90, "lead_time_category"] = 4
df1.loc[df1["lead_time"] > 120, "lead_time_category"] = 5
df1.loc[df1["lead_time"] > 150, "lead_time_category"] = 6
df1.loc[df1["lead_time"] > 180, "lead_time_category"] = 7
df1.loc[df1["lead_time"] > 210, "lead_time_category"] = 8
df1.loc[df1["lead_time"] > 240, "lead_time_category"] = 9
df1.loc[df1["lead_time"] > 270, "lead_time_category"] = 10
df1.loc[df1["lead_time"] > 300, "lead_time_category"] = 11
df1.loc[df1["lead_time"] > 330, "lead_time_category"] = 12


df1.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 36275 entries, 0 to 36274
Data columns (total 29 columns):
 #   Column                                Non-Null Count  Dtype  
---  ------                                --------------  -----  
 0   no_of_adults                          36275 non-null  int64  
 1   no_of_children                        36275 non-null  int64  
 2   no_of_weekend_nights                  36275 non-null  int64  
 3   no_of_week_nights                     36275 non-null  int64  
 4   type_of_meal_plan                     36275 non-null  int64  
 5   required_car_parking_space            36275 non-null  int64  
 6   lead_time                             36275 non-null  int64  
 7   arrival_year                          36275 non-null  int64  
 8   arrival_month                         36275 non-null  int64  
 9   arrival_date                          36275 non-null  int64  
 10  repeated_guest                        36275 non-null  int64  
 11  no_of_previous_cancellations          36275 non-null  int64  
 12  no_of_previous_bookings_not_canceled  36275 non-null  int64  
 13  avg_price_per_room                    36275 non-null  float64
 14  no_of_special_requests                36275 non-null  int64  
 15  booking_status                        36275 non-null  float64
 16  room_type_reserved_Room_Type 1        36275 non-null  uint8  
 17  room_type_reserved_Room_Type 2        36275 non-null  uint8  
 18  room_type_reserved_Room_Type 3        36275 non-null  uint8  
 19  room_type_reserved_Room_Type 4        36275 non-null  uint8  
 20  room_type_reserved_Room_Type 5        36275 non-null  uint8  
 21  room_type_reserved_Room_Type 6        36275 non-null  uint8  
 22  room_type_reserved_Room_Type 7        36275 non-null  uint8  
 23  market_segment_type_Aviation          36275 non-null  uint8  
 24  market_segment_type_Complementary     36275 non-null  uint8  
 25  market_segment_type_Corporate         36275 non-null  uint8  
 26  market_segment_type_Offline           36275 non-null  uint8  
 27  market_segment_type_Online            36275 non-null  uint8  
 28  lead_time_category                    36275 non-null  float64
dtypes: float64(3), int64(14), uint8(12)
memory usage: 5.1 MB


df1.isnull().sum()

no_of_adults                            0
no_of_children                          0
no_of_weekend_nights                    0
no_of_week_nights                       0
type_of_meal_plan                       0
required_car_parking_space              0
lead_time                               0
arrival_year                            0
arrival_month                           0
arrival_date                            0
repeated_guest                          0
no_of_previous_cancellations            0
no_of_previous_bookings_not_canceled    0
avg_price_per_room                      0
no_of_special_requests                  0
booking_status                          0
room_type_reserved_Room_Type 1          0
room_type_reserved_Room_Type 2          0
room_type_reserved_Room_Type 3          0
room_type_reserved_Room_Type 4          0
room_type_reserved_Room_Type 5          0
room_type_reserved_Room_Type 6          0
room_type_reserved_Room_Type 7          0
market_segment_type_Aviation            0
market_segment_type_Complementary       0
market_segment_type_Corporate           0
market_segment_type_Offline             0
market_segment_type_Online              0
lead_time_category                      0
dtype: int64


numerical_col = df1.select_dtypes(include=np.number).columns.tolist()
plt.figure(figsize=(20, 30))

for i, variable in enumerate(numerical_col):
    plt.subplot(6, 5, i + 1)
    plt.boxplot(df1[variable], whis=1.5)
    plt.tight_layout()
    plt.title(variable)

plt.show()


# functions to treat outliers by flooring and capping


def treat_outliers(df, col):
    """
    Treats outliers in a variable

    df: dataframe
    col: dataframe column
    """
    Q1 = df[col].quantile(0.25)  # 25th quantile
    Q3 = df[col].quantile(0.75)  # 75th quantile
    IQR = Q3 - Q1
    Lower_Whisker = Q1 - 1.5 * IQR
    Upper_Whisker = Q3 + 1.5 * IQR

    # all the values smaller than Lower_Whisker will be assigned the value of Lower_Whisker
    # all the values greater than Upper_Whisker will be assigned the value of Upper_Whisker
    df[col] = np.clip(df[col], Lower_Whisker, Upper_Whisker)

    return df


def treat_outliers_all(df, col_list):
    """
    Treat outliers in a list of variables

    df: dataframe
    col_list: list of dataframe columns
    """
    for c in col_list:
        df = treat_outliers(df, c)

    return df


selected_col = [
    "avg_price_per_room",
    "lead_time",
    "no_of_week_nights",
    "no_of_weekend_nights",
]
df2 = treat_outliers_all(df1, selected_col)


numerical_col = df1.select_dtypes(include=np.number).columns.tolist()
plt.figure(figsize=(20, 30))

for i, variable in enumerate(numerical_col):
    plt.subplot(6, 5, i + 1)
    plt.boxplot(df2[variable], whis=1.5)
    plt.tight_layout()
    plt.title(variable)

plt.show()


plt.figure(figsize=(12, 6))

sns.countplot(data=df2, x="lead_time_category", hue="booking_status")
plt.show()


distribution_plot_wrt_target(df2, "lead_time", "booking_status")


numerical_col = df2.select_dtypes(include=np.number).columns.tolist()
plt.figure(figsize=(20, 20))

for i, variable in enumerate(numerical_col):
    plt.subplot(6, 5, i + 1)
    plt.hist(df2[variable])
    plt.tight_layout()
    plt.title(variable)

plt.show()


df2.drop(
    ["lead_time_category"], axis=1, inplace=True
)  # drop lead_time_category column as this information is not used more.

X = df2.drop(["booking_status"], axis=1)
Y = df2["booking_status"]

# creating dummies
X = pd.get_dummies(X, drop_first=True)

# Splitting data in train and test sets
X_train, X_test, y_train, y_test = train_test_split(
    X, Y, test_size=0.30, random_state=1, stratify=Y
)


print("Shape of Training set : ", X_train.shape)
print("Shape of test set : ", X_test.shape)
print("Percentage of classes in training set:")
print(y_train.value_counts(normalize=True))
print("Percentage of classes in test set:")
print(y_test.value_counts(normalize=True))

Shape of Training set :  (25392, 27)
Shape of test set :  (10883, 27)
Percentage of classes in training set:
0.0    0.672377
1.0    0.327623
Name: booking_status, dtype: float64
Percentage of classes in test set:
0.0    0.672333
1.0    0.327667
Name: booking_status, dtype: float64


accuracy_score(y_train, np.ones_like(y_train))

0.3276228733459357


recall_score(y_train, np.ones_like(y_train))

1.0


precision_score(y_train, np.ones_like(y_train))

0.3276228733459357


f1_score(y_train, np.ones_like(y_train))

0.4935481000266975


# defining a function to compute different metrics to check performance of a classification model built using statsmodels
def model_performance_classification_statsmodels(
    model, predictors, target, threshold=0.5
):
    """
    Function to compute different metrics to check classification model performance

    model: classifier
    predictors: independent variables
    target: dependent variable
    threshold: threshold for classifying the observation as class 1
    """

    # checking which probabilities are greater than threshold
    pred_temp = model.predict(predictors) > threshold
    # rounding off the above values to get classes
    pred = np.round(pred_temp)

    acc = accuracy_score(target, pred)  # to compute Accuracy
    recall = recall_score(target, pred)  # to compute Recall
    precision = precision_score(target, pred)  # to compute Precision
    f1 = f1_score(target, pred)  # to compute F1-score

    # creating a dataframe of metrics
    df_perf = pd.DataFrame(
        {"Accuracy": acc, "Recall": recall, "Precision": precision, "F1": f1,},
        index=[0],
    )

    return df_perf


# defining a function to plot the confusion_matrix of a classification model


def confusion_matrix_statsmodels(model, predictors, target, threshold=0.5):
    """
    To plot the confusion_matrix with percentages

    model: classifier
    predictors: independent variables
    target: dependent variable
    threshold: threshold for classifying the observation as class 1
    """
    y_pred = model.predict(predictors) > threshold
    cm = confusion_matrix(target, y_pred)
    labels = np.asarray(
        [
            ["{0:0.0f}".format(item) + "\n{0:.2%}".format(item / cm.flatten().sum())]
            for item in cm.flatten()
        ]
    ).reshape(2, 2)

    plt.figure(figsize=(6, 4))
    sns.heatmap(cm, annot=labels, fmt="")
    plt.ylabel("True label")
    plt.xlabel("Predicted label")


X = df2.drop(["booking_status"], axis=1)
Y = df2["booking_status"]

# adding a contstant to X variable
X = add_constant(X)

# creating dummies
X = pd.get_dummies(X, drop_first=True)

# Splitting data in train and test sets
X_train, X_test, y_train, y_test = train_test_split(
    X, Y, test_size=0.30, random_state=1, stratify=Y
)


# fitting the model on training set
logit = sm.Logit(y_train, X_train)
lg = logit.fit()

Warning: Maximum number of iterations has been exceeded.
         Current function value: 0.422920
         Iterations: 35

C:\Anacoda\lib\site-packages\statsmodels\base\model.py:566: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
  warnings.warn("Maximum Likelihood optimization failed to "


# let's print the logistic regression summary
print(lg.summary())

                           Logit Regression Results                           
==============================================================================
Dep. Variable:         booking_status   No. Observations:                25392
Model:                          Logit   Df Residuals:                    25366
Method:                           MLE   Df Model:                           25
Date:                Fri, 25 Mar 2022   Pseudo R-squ.:                  0.3313
Time:                        18:48:29   Log-Likelihood:                -10739.
converged:                      False   LL-Null:                       -16060.
Covariance Type:            nonrobust   LLR p-value:                     0.000
========================================================================================================
                                           coef    std err          z      P>|z|      [0.025      0.975]
--------------------------------------------------------------------------------------------------------
const                                 -636.8479   7.41e+05     -0.001      0.999   -1.45e+06    1.45e+06
no_of_adults                             0.0414      0.038      1.098      0.272      -0.032       0.115
no_of_children                           0.0834      0.061      1.378      0.168      -0.035       0.202
no_of_weekend_nights                     0.1491      0.020      7.566      0.000       0.110       0.188
no_of_week_nights                        0.0011      0.014      0.083      0.934      -0.026       0.028
type_of_meal_plan                       -0.0543      0.025     -2.172      0.030      -0.103      -0.005
required_car_parking_space              -1.6519      0.138    -11.968      0.000      -1.922      -1.381
lead_time                                0.0166      0.000     60.448      0.000       0.016       0.017
arrival_year                             0.4204      0.059      7.101      0.000       0.304       0.536
arrival_month                           -0.0475      0.006     -7.311      0.000      -0.060      -0.035
arrival_date                             0.0035      0.002      1.790      0.073      -0.000       0.007
repeated_guest                          -1.7140      0.701     -2.446      0.014      -3.087      -0.341
no_of_previous_cancellations             0.3378      0.102      3.326      0.001       0.139       0.537
no_of_previous_bookings_not_canceled    -1.5389      0.952     -1.616      0.106      -3.405       0.328
avg_price_per_room                       0.0201      0.001     25.854      0.000       0.019       0.022
no_of_special_requests                  -1.4885      0.030    -49.012      0.000      -1.548      -1.429
room_type_reserved_Room_Type 1         -90.6932        nan        nan        nan         nan         nan
room_type_reserved_Room_Type 2         -91.1131        nan        nan        nan         nan         nan
room_type_reserved_Room_Type 3         -89.5603        nan        nan        nan         nan         nan
room_type_reserved_Room_Type 4         -91.0142        nan        nan        nan         nan         nan
room_type_reserved_Room_Type 5         -91.3891        nan        nan        nan         nan         nan
room_type_reserved_Room_Type 6         -91.3312        nan        nan        nan         nan         nan
room_type_reserved_Room_Type 7         -91.5691        nan        nan        nan         nan         nan
market_segment_type_Aviation          -123.4026        nan        nan        nan         nan         nan
market_segment_type_Complementary     -140.3886        nan        nan        nan         nan         nan
market_segment_type_Corporate         -124.3430        nan        nan        nan         nan         nan
market_segment_type_Offline           -125.2120        nan        nan        nan         nan         nan
market_segment_type_Online            -123.4804        nan        nan        nan         nan         nan
========================================================================================================


print("Training performance:")
model_performance_classification_statsmodels(lg, X_train, y_train)

Training performance:


vif_series = pd.Series(
    [variance_inflation_factor(X_train.values, i) for i in range(X_train.shape[1])],
    index=X_train.columns,
    dtype=float,
)
print(
    "Series before feature selection: \n\n{}\n".format(
        vif_series.sort_values(ascending=False)
    )
)

C:\Anacoda\lib\site-packages\statsmodels\regression\linear_model.py:1715: RuntimeWarning: divide by zero encountered in double_scalars
  return 1 - self.ssr/self.centered_tss
C:\Anacoda\lib\site-packages\statsmodels\stats\outliers_influence.py:193: RuntimeWarning: divide by zero encountered in double_scalars
  vif = 1. / (1. - r_squared_i)

Series before feature selection: 

market_segment_type_Online                   inf
room_type_reserved_Room_Type 1               inf
market_segment_type_Offline                  inf
market_segment_type_Corporate                inf
market_segment_type_Complementary            inf
market_segment_type_Aviation                 inf
room_type_reserved_Room_Type 7               inf
room_type_reserved_Room_Type 6               inf
room_type_reserved_Room_Type 5               inf
room_type_reserved_Room_Type 4               inf
room_type_reserved_Room_Type 3               inf
room_type_reserved_Room_Type 2               inf
no_of_children                          1.999380
avg_price_per_room                      1.896121
repeated_guest                          1.750991
no_of_previous_bookings_not_canceled    1.570349
arrival_year                            1.403503
type_of_meal_plan                       1.399971
lead_time                               1.370191
no_of_adults                            1.348639
no_of_previous_cancellations            1.321870
arrival_month                           1.272803
no_of_special_requests                  1.248451
no_of_week_nights                       1.088057
no_of_weekend_nights                    1.051674
required_car_parking_space              1.034406
arrival_date                            1.006699
const                                   0.000000
dtype: float64


X_train1 = X_train.drop(
    [
        "market_segment_type_Online",
        "market_segment_type_Offline",
        "market_segment_type_Corporate",
        "market_segment_type_Complementary",
        "market_segment_type_Aviation",
    ],
    axis=1,
)


vif_series2 = pd.Series(
    [variance_inflation_factor(X_train1.values, i) for i in range(X_train1.shape[1])],
    index=X_train1.columns,
)
print(
    "Series before feature selection: \n\n{}\n".format(
        vif_series2.sort_values(ascending=False)
    )
)

Series before feature selection: 

room_type_reserved_Room_Type 7               inf
room_type_reserved_Room_Type 6               inf
room_type_reserved_Room_Type 5               inf
room_type_reserved_Room_Type 4               inf
room_type_reserved_Room_Type 3               inf
room_type_reserved_Room_Type 2               inf
room_type_reserved_Room_Type 1               inf
no_of_children                          1.990595
avg_price_per_room                      1.610823
repeated_guest                          1.559362
no_of_previous_bookings_not_canceled    1.556637
arrival_year                            1.389348
no_of_previous_cancellations            1.307243
lead_time                               1.294502
no_of_adults                            1.293707
arrival_month                           1.265042
type_of_meal_plan                       1.203315
no_of_special_requests                  1.134035
no_of_week_nights                       1.076705
no_of_weekend_nights                    1.036531
required_car_parking_space              1.029296
arrival_date                            1.006091
const                                   0.000000
dtype: float64


logit1 = sm.Logit(y_train, X_train1.astype(float))
lg1 = logit1.fit()

print("Training performance:")
model_performance_classification_statsmodels(lg1, X_train1, y_train)

Optimization terminated successfully.
         Current function value: 0.448115
         Iterations 15
Training performance:


X_train2 = X_train1.drop(
    [
        "room_type_reserved_Room_Type 1",
        "room_type_reserved_Room_Type 2",
        "room_type_reserved_Room_Type 3",
        "room_type_reserved_Room_Type 4",
        "room_type_reserved_Room_Type 5",
        "room_type_reserved_Room_Type 6",
        "room_type_reserved_Room_Type 7",
    ],
    axis=1,
)


vif_series3 = pd.Series(
    [variance_inflation_factor(X_train2.values, i) for i in range(X_train2.shape[1])],
    index=X_train2.columns,
)
print(
    "Series before feature selection: \n\n{}\n".format(
        vif_series3.sort_values(ascending=False)
    )
)

Series before feature selection: 

const                                   3.791137e+07
no_of_previous_bookings_not_canceled    1.554995e+00
repeated_guest                          1.551673e+00
avg_price_per_room                      1.452163e+00
arrival_year                            1.372549e+00
no_of_previous_cancellations            1.306709e+00
arrival_month                           1.263378e+00
lead_time                               1.260392e+00
no_of_adults                            1.224156e+00
type_of_meal_plan                       1.170730e+00
no_of_children                          1.138765e+00
no_of_special_requests                  1.126482e+00
no_of_week_nights                       1.065280e+00
no_of_weekend_nights                    1.034507e+00
required_car_parking_space              1.028674e+00
arrival_date                            1.005543e+00
dtype: float64


logit2 = sm.Logit(y_train, X_train2.astype(float))
lg2 = logit2.fit()

print("Training performance:")
model_performance_classification_statsmodels(lg2, X_train2, y_train)

Optimization terminated successfully.
         Current function value: 0.449142
         Iterations 16
Training performance:


print(lg2.summary())

                           Logit Regression Results                           
==============================================================================
Dep. Variable:         booking_status   No. Observations:                25392
Model:                          Logit   Df Residuals:                    25376
Method:                           MLE   Df Model:                           15
Date:                Fri, 25 Mar 2022   Pseudo R-squ.:                  0.2899
Time:                        18:48:36   Log-Likelihood:                -11405.
converged:                       True   LL-Null:                       -16060.
Covariance Type:            nonrobust   LLR p-value:                     0.000
========================================================================================================
                                           coef    std err          z      P>|z|      [0.025      0.975]
--------------------------------------------------------------------------------------------------------
const                                -1212.5748    115.100    -10.535      0.000   -1438.166    -986.984
no_of_adults                             0.0919      0.035      2.651      0.008       0.024       0.160
no_of_children                           0.0565      0.043      1.316      0.188      -0.028       0.141
no_of_weekend_nights                     0.2033      0.019     10.740      0.000       0.166       0.240
no_of_week_nights                        0.0307      0.013      2.359      0.018       0.005       0.056
type_of_meal_plan                       -0.3631      0.022    -16.310      0.000      -0.407      -0.319
required_car_parking_space              -1.4072      0.134    -10.471      0.000      -1.671      -1.144
lead_time                                0.0144      0.000     59.006      0.000       0.014       0.015
arrival_year                             0.5991      0.057     10.503      0.000       0.487       0.711
arrival_month                           -0.0498      0.006     -7.911      0.000      -0.062      -0.037
arrival_date                             0.0043      0.002      2.295      0.022       0.001       0.008
repeated_guest                          -1.4860      0.560     -2.652      0.008      -2.584      -0.388
no_of_previous_cancellations             0.3042      0.101      3.020      0.003       0.107       0.502
no_of_previous_bookings_not_canceled    -1.7557      0.990     -1.773      0.076      -3.696       0.185
avg_price_per_room                       0.0231      0.001     33.401      0.000       0.022       0.024
no_of_special_requests                  -1.1765      0.027    -42.887      0.000      -1.230      -1.123
========================================================================================================


# running a loop to drop variables with high p-value

# initial list of columns
cols = X_train2.columns.tolist()

# setting an initial max p-value
max_p_value = 1

while len(cols) > 0:
    # defining the train set
    X_train_aux = X_train2[cols]

    # fitting the model
    model = sm.Logit(y_train, X_train_aux).fit(disp=False)

    # getting the p-values and the maximum p-value
    p_values = model.pvalues
    max_p_value = max(p_values)

    # name of the variable with maximum p-value
    feature_with_p_max = p_values.idxmax()

    if max_p_value > 0.05:
        cols.remove(feature_with_p_max)
    else:
        break

selected_features = cols
print(selected_features)

['const', 'no_of_adults', 'no_of_weekend_nights', 'no_of_week_nights', 'type_of_meal_plan', 'required_car_parking_space', 'lead_time', 'arrival_year', 'arrival_month', 'arrival_date', 'repeated_guest', 'no_of_previous_cancellations', 'avg_price_per_room', 'no_of_special_requests']


X_train3 = X_train2[selected_features]


logit3 = sm.Logit(y_train, X_train3.astype(float))
lg3 = logit3.fit()

print(lg3.summary())

Optimization terminated successfully.
         Current function value: 0.449404
         Iterations 11
                           Logit Regression Results                           
==============================================================================
Dep. Variable:         booking_status   No. Observations:                25392
Model:                          Logit   Df Residuals:                    25378
Method:                           MLE   Df Model:                           13
Date:                Fri, 25 Mar 2022   Pseudo R-squ.:                  0.2895
Time:                        18:48:39   Log-Likelihood:                -11411.
converged:                       True   LL-Null:                       -16060.
Covariance Type:            nonrobust   LLR p-value:                     0.000
================================================================================================
                                   coef    std err          z      P>|z|      [0.025      0.975]
------------------------------------------------------------------------------------------------
const                        -1202.1109    115.119    -10.442      0.000   -1427.741    -976.481
no_of_adults                     0.0857      0.034      2.500      0.012       0.019       0.153
no_of_weekend_nights             0.2044      0.019     10.804      0.000       0.167       0.241
no_of_week_nights                0.0316      0.013      2.425      0.015       0.006       0.057
type_of_meal_plan               -0.3643      0.022    -16.367      0.000      -0.408      -0.321
required_car_parking_space      -1.4025      0.134    -10.450      0.000      -1.666      -1.139
lead_time                        0.0144      0.000     59.125      0.000       0.014       0.015
arrival_year                     0.5939      0.057     10.410      0.000       0.482       0.706
arrival_month                   -0.0501      0.006     -7.962      0.000      -0.062      -0.038
arrival_date                     0.0043      0.002      2.274      0.023       0.001       0.008
repeated_guest                  -2.5366      0.453     -5.594      0.000      -3.425      -1.648
no_of_previous_cancellations     0.2363      0.077      3.083      0.002       0.086       0.386
avg_price_per_room               0.0234      0.001     35.833      0.000       0.022       0.025
no_of_special_requests          -1.1753      0.027    -42.961      0.000      -1.229      -1.122
================================================================================================


print("Training performance:")
model_performance_classification_statsmodels(lg3, X_train3, y_train)

Training performance:


# converting coefficients to odds
odds = np.exp(lg3.params)

# finding the percentage change
perc_change_odds = (np.exp(lg3.params) - 1) * 100

# removing limit from number of columns to display
pd.set_option("display.max_columns", None)

# adding the odds to a dataframe
pd.DataFrame({"Odds": odds, "Change_odd%": perc_change_odds}, index=X_train3.columns).T


# creating confusion matrix
confusion_matrix_statsmodels(lg3, X_train3, y_train, threshold=0.5)


print("Training performance:")
log_reg_model_train_perf = model_performance_classification_statsmodels(
    lg3, X_train3, y_train, threshold=0.5
)
log_reg_model_train_perf

Training performance:


logit_roc_auc_train = roc_auc_score(y_train, lg3.predict(X_train3))
fpr, tpr, thresholds = roc_curve(y_train, lg3.predict(X_train3))
plt.figure(figsize=(7, 5))
plt.plot(fpr, tpr, label="Logistic Regression (area = %0.2f)" % logit_roc_auc_train)
plt.plot([0, 1], [0, 1], "r--")
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel("False Positive Rate")
plt.ylabel("True Positive Rate")
plt.title("Receiver operating characteristic")
plt.legend(loc="lower right")
plt.show()


# Optimal threshold as per AUC-ROC curve
# The optimal cut off would be where tpr is high and fpr is low
fpr, tpr, thresholds = roc_curve(y_train, lg3.predict(X_train3))

optimal_idx = np.argmax(tpr - fpr)
optimal_threshold_auc_roc = thresholds[optimal_idx]
print(optimal_threshold_auc_roc)

0.3178870183397934


# creating confusion matrix
confusion_matrix_statsmodels(
    lg3, X_train3, y_train, threshold=optimal_threshold_auc_roc
)


# checking model performance for this model
log_reg_model_train_perf_threshold_auc_roc = model_performance_classification_statsmodels(
    lg3, X_train3, y_train, threshold=optimal_threshold_auc_roc
)
print("Training performance:")
log_reg_model_train_perf_threshold_auc_roc

Training performance:


y_scores = lg3.predict(X_train3)
prec, rec, tre = precision_recall_curve(y_train, y_scores,)


def plot_prec_recall_vs_tresh(precisions, recalls, thresholds):
    plt.plot(thresholds, precisions[:-1], "b--", label="precision")
    plt.plot(thresholds, recalls[:-1], "g--", label="recall")
    plt.xlabel("Threshold")
    plt.legend(loc="upper left")
    plt.ylim([0, 1])


plt.figure(figsize=(10, 7))
plot_prec_recall_vs_tresh(prec, rec, tre)
plt.show()


# setting the threshold
optimal_threshold_curve = 0.42


# creating confusion matrix
confusion_matrix_statsmodels(lg3, X_train3, y_train, threshold=optimal_threshold_curve)


log_reg_model_train_perf_threshold_curve = model_performance_classification_statsmodels(
    lg3, X_train3, y_train, threshold=optimal_threshold_curve
)
print("Training performance:")
log_reg_model_train_perf_threshold_curve

Training performance:


# training performance comparison

models_train_comp_df = pd.concat(
    [
        log_reg_model_train_perf.T,
        log_reg_model_train_perf_threshold_auc_roc.T,
        log_reg_model_train_perf_threshold_curve.T,
    ],
    axis=1,
)
models_train_comp_df.columns = [
    "Logistic Regression-default Threshold (0.5)",
    "Logistic Regression-0.31 Threshold",
    "Logistic Regression-0.42 Threshold",
]

print("Training performance comparison:")
models_train_comp_df

Training performance comparison:


X_test3 = X_test[list(X_train3.columns)]


# creating confusion matrix
confusion_matrix_statsmodels(lg3, X_test3, y_test)


log_reg_model_test_perf = model_performance_classification_statsmodels(
    lg3, X_test3, y_test
)

print("Test performance:")
log_reg_model_test_perf

Test performance:


logit_roc_auc_train = roc_auc_score(y_test, lg3.predict(X_test3))
fpr, tpr, thresholds = roc_curve(y_test, lg3.predict(X_test3))
plt.figure(figsize=(7, 5))
plt.plot(fpr, tpr, label="Logistic Regression (area = %0.2f)" % logit_roc_auc_train)
plt.plot([0, 1], [0, 1], "r--")
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel("False Positive Rate")
plt.ylabel("True Positive Rate")
plt.title("Receiver operating characteristic")
plt.legend(loc="lower right")
plt.show()


# creating confusion matrix
confusion_matrix_statsmodels(lg3, X_test3, y_test, threshold=optimal_threshold_auc_roc)


# checking model performance for this model
log_reg_model_test_perf_threshold_auc_roc = model_performance_classification_statsmodels(
    lg3, X_test3, y_test, threshold=optimal_threshold_auc_roc
)
print("Test performance:")
log_reg_model_test_perf_threshold_auc_roc

Test performance:


# creating confusion matrix
confusion_matrix_statsmodels(lg3, X_test3, y_test, threshold=optimal_threshold_curve)


log_reg_model_test_perf_threshold_curve = model_performance_classification_statsmodels(
    lg3, X_test3, y_test, threshold=optimal_threshold_curve
)
print("Test performance:")
log_reg_model_test_perf_threshold_curve

Test performance:


# training performance comparison

models_train_comp_df = pd.concat(
    [
        log_reg_model_train_perf.T,
        log_reg_model_train_perf_threshold_auc_roc.T,
        log_reg_model_train_perf_threshold_curve.T,
    ],
    axis=1,
)
models_train_comp_df.columns = [
    "Logistic Regression-default Threshold (0.5)",
    "Logistic Regression-0.31 Threshold",
    "Logistic Regression-0.42 Threshold",
]

print("Training performance comparison:")
models_train_comp_df

Training performance comparison:


# testing performance comparison

models_test_comp_df = pd.concat(
    [
        log_reg_model_test_perf.T,
        log_reg_model_test_perf_threshold_auc_roc.T,
        log_reg_model_test_perf_threshold_curve.T,
    ],
    axis=1,
)
models_test_comp_df.columns = [
    "Logistic Regression-default Threshold (0.5)",
    "Logistic Regression-0.31 Threshold",
    "Logistic Regression-0.42 Threshold",
]

print("Test set performance comparison:")
models_test_comp_df

Test set performance comparison:


X = df2.drop(["booking_status"], axis=1)
Y = df2["booking_status"]

# Splitting data in train and test sets
X_train, X_test, y_train, y_test = train_test_split(
    X, Y, test_size=0.30, random_state=1
)


# defining a function to compute different metrics to check performance of a classification model built using sklearn
def model_performance_classification_sklearn(model, predictors, target):
    """
    Function to compute different metrics to check classification model performance

    model: classifier
    predictors: independent variables
    target: dependent variable
    """

    # predicting using the independent variables
    pred = model.predict(predictors)

    acc = accuracy_score(target, pred)  # to compute Accuracy
    recall = recall_score(target, pred)  # to compute Recall
    precision = precision_score(target, pred)  # to compute Precision
    f1 = f1_score(target, pred)  # to compute F1-score

    # creating a dataframe of metrics
    df_perf = pd.DataFrame(
        {"Accuracy": acc, "Recall": recall, "Precision": precision, "F1": f1,},
        index=[0],
    )

    return df_perf


def confusion_matrix_sklearn(model, predictors, target):
    """
    To plot the confusion_matrix with percentages

    model: classifier
    predictors: independent variables
    target: dependent variable
    """
    y_pred = model.predict(predictors)
    cm = confusion_matrix(target, y_pred)
    labels = np.asarray(
        [
            ["{0:0.0f}".format(item) + "\n{0:.2%}".format(item / cm.flatten().sum())]
            for item in cm.flatten()
        ]
    ).reshape(2, 2)

    plt.figure(figsize=(6, 4))
    sns.heatmap(cm, annot=labels, fmt="")
    plt.ylabel("True label")
    plt.xlabel("Predicted label")


dTree = DecisionTreeClassifier(criterion="gini", random_state=1)
dTree.fit(X_train, y_train)

DecisionTreeClassifier(random_state=1)


confusion_matrix_sklearn(dTree, X_train, y_train)


decision_tree_perf_train = model_performance_classification_sklearn(
    dTree, X_train, y_train
)
decision_tree_perf_train


confusion_matrix_sklearn(dTree, X_test, y_test)


decision_tree_perf_test = model_performance_classification_sklearn(
    dTree, X_test, y_test
)
decision_tree_perf_test


feature_names = list(X.columns)

plt.figure(figsize=(20, 30))
tree.plot_tree(
    dTree,
    feature_names=feature_names,
    filled=True,
    fontsize=9,
    node_ids=True,
    class_names=True,
)
plt.show()


# Text report showing the rules of a decision tree -

print(tree.export_text(dTree, feature_names=feature_names, show_weights=True))

|--- lead_time <= 151.50
|   |--- no_of_special_requests <= 0.50
|   |   |--- market_segment_type_Online <= 0.50
|   |   |   |--- lead_time <= 90.50
|   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |--- avg_price_per_room <= 179.47
|   |   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |   |--- lead_time <= 16.50
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |   |--- repeated_guest <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 11.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 13
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  11.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- repeated_guest >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [147.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 29.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- arrival_date >  29.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_children <= 1.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_children >  1.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  16.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 135.00
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 17.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  17.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [29.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  135.00
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 8.00] class: 1.0
|   |   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |   |--- weights: [1606.00, 0.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  179.47
|   |   |   |   |   |   |--- arrival_date <= 25.50
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 <= 0.50
|   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 >  0.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 16.00] class: 1.0
|   |   |   |   |   |   |--- arrival_date >  25.50
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 <= 0.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 >  0.50
|   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |--- lead_time <= 68.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 4.50
|   |   |   |   |   |   |   |--- lead_time <= 1.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 5.50
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  5.50
|   |   |   |   |   |   |   |   |   |   |--- market_segment_type_Aviation <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- market_segment_type_Aviation >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 4.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 33.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  4.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  1.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 59.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 16
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12
|   |   |   |   |   |   |   |   |   |--- lead_time >  59.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [22.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Aviation <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 65.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 13
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  65.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Aviation >  0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |--- no_of_weekend_nights >  4.50
|   |   |   |   |   |   |   |--- weights: [0.00, 8.00] class: 1.0
|   |   |   |   |   |--- lead_time >  68.50
|   |   |   |   |   |   |--- avg_price_per_room <= 99.98
|   |   |   |   |   |   |   |--- arrival_month <= 3.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 62.50
|   |   |   |   |   |   |   |   |   |--- weights: [21.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  62.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 77.00
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 9.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  77.00
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [9.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |--- arrival_month >  3.50
|   |   |   |   |   |   |   |   |--- lead_time <= 71.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |--- lead_time >  71.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 88.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  88.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 73.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  73.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |--- avg_price_per_room >  99.98
|   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 17.00
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 52.00] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_date >  17.00
|   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 105.20
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 22.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 75.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  75.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- arrival_date >  22.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 78.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 22.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  78.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  105.20
|   |   |   |   |   |   |   |   |   |--- lead_time <= 88.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 3.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  3.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- lead_time >  88.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |--- lead_time >  90.50
|   |   |   |   |--- lead_time <= 117.50
|   |   |   |   |   |--- avg_price_per_room <= 93.58
|   |   |   |   |   |   |--- arrival_date <= 6.50
|   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 80.38
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  80.38
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 5.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  5.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 5.50
|   |   |   |   |   |   |   |   |   |--- weights: [35.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  5.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 75.22
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  75.22
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |--- arrival_date >  6.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 66.50
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  9.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [24.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 58.75
|   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  58.75
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 97.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  97.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 39.00] class: 1.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  66.50
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 29.50
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11
|   |   |   |   |   |   |   |   |   |--- arrival_date >  29.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 96.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  96.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 82.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 102.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 7.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  102.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  82.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 99.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  99.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.00, 2.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  93.58
|   |   |   |   |   |   |--- arrival_date <= 16.50
|   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |--- lead_time <= 108.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 107.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 125.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  125.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  107.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |--- lead_time >  108.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 111.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  111.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [12.00, 1.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 108.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 14.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 113.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  113.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- arrival_date >  14.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 47.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  108.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [42.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 9.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  9.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |--- arrival_date >  16.50
|   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 127.39
|   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 50.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  127.39
|   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 101.34
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  101.34
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 165.11
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  165.11
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |--- lead_time >  117.50
|   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |--- arrival_date <= 7.50
|   |   |   |   |   |   |   |--- weights: [51.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_date >  7.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 93.58
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 65.38
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  65.38
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 89.88
|   |   |   |   |   |   |   |   |   |   |--- weights: [24.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  89.88
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 10.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.00, 2.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  10.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  93.58
|   |   |   |   |   |   |   |   |--- arrival_date <= 28.00
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 17.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 1.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 118.38
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  118.38
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  28.00
|   |   |   |   |   |   |   |   |   |--- weights: [13.00, 1.00] class: 0.0
|   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |--- weights: [113.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |--- lead_time <= 125.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 90.85
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 87.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  87.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 10.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  90.85
|   |   |   |   |   |   |   |   |   |--- weights: [14.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  125.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 155.78
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 10.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  10.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9
|   |   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 128.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  128.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [75.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  155.78
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |--- market_segment_type_Online >  0.50
|   |   |   |--- lead_time <= 13.50
|   |   |   |   |--- avg_price_per_room <= 119.42
|   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |--- weights: [128.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |--- lead_time <= 3.50
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 106.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 74.57
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [37.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  74.57
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 15
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  106.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [38.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.00
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 75.46
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  75.46
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- arrival_date >  27.00
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 12.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  3.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 99.38
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 3.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [14.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  3.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 12.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  12.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [9.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  99.38
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 117.25
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 101.67
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 7.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  101.67
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  117.25
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.00, 0.00] class: 0.0
|   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 117.56
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- weights: [148.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 8.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  8.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [69.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  117.56
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |--- lead_time <= 10.00
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 25.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  25.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  10.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 5.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |--- avg_price_per_room >  119.42
|   |   |   |   |   |--- lead_time <= 3.50
|   |   |   |   |   |   |--- avg_price_per_room <= 178.78
|   |   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 134.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  134.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 136.09
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  136.09
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9
|   |   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 169.67
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 5.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  5.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [53.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  169.67
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 172.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  172.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |--- avg_price_per_room >  178.78
|   |   |   |   |   |   |   |--- arrival_date <= 15.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 10.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 6.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_date >  10.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 7.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_date >  15.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 24.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 22.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  22.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  24.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |--- lead_time >  3.50
|   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- lead_time <= 6.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |--- lead_time >  6.50
|   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- no_of_adults <= 2.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 160.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 6.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  6.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  160.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 25.00] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_adults >  2.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 5.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 15.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  15.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  5.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 6.00] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |--- arrival_date <= 14.00
|   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 9.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  9.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |--- weights: [7.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_date >  14.00
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 161.17
|   |   |   |   |   |   |   |   |   |--- lead_time <= 12.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [30.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  12.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  161.17
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 166.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  166.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_children <= 1.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_children >  1.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |--- lead_time >  13.50
|   |   |   |   |--- avg_price_per_room <= 105.27
|   |   |   |   |   |--- avg_price_per_room <= 60.07
|   |   |   |   |   |   |--- lead_time <= 84.50
|   |   |   |   |   |   |   |--- lead_time <= 51.50
|   |   |   |   |   |   |   |   |--- lead_time <= 50.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 29.04
|   |   |   |   |   |   |   |   |   |   |--- weights: [19.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  29.04
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 49.84
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  49.84
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |--- lead_time >  50.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  51.50
|   |   |   |   |   |   |   |   |--- weights: [32.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  84.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 19.00
|   |   |   |   |   |   |   |   |   |--- lead_time <= 139.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 8.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  139.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  19.00
|   |   |   |   |   |   |   |   |   |--- lead_time <= 87.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  87.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 59.43
|   |   |   |   |   |   |   |   |   |--- weights: [14.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  59.43
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |--- avg_price_per_room >  60.07
|   |   |   |   |   |   |--- lead_time <= 25.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [29.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 14.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  14.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 14
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- weights: [54.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  25.50
|   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 5.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  5.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 15
|   |   |   |   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 60.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  60.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 28
|   |   |   |   |   |   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [12.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 5.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  5.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 57.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  57.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 35.00] class: 1.0
|   |   |   |   |--- avg_price_per_room >  105.27
|   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |--- arrival_month <= 10.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [12.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 13.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 <= 0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 171.22
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 24.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 23
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  24.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 16
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  171.22
|   |   |   |   |   |   |   |   |   |   |--- no_of_children <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- no_of_children >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 >  0.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 26.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 175.71
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  175.71
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  26.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 5.00] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  10.50
|   |   |   |   |   |   |   |--- lead_time <= 22.50
|   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 4.00] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |--- weights: [22.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  22.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 168.06
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 147.75
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  147.75
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 15.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  168.06
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 5.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 80.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  80.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  5.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 3.00
|   |   |   |   |   |   |   |--- weights: [39.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  3.00
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |--- no_of_special_requests >  0.50
|   |   |--- no_of_special_requests <= 1.50
|   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |--- lead_time <= 63.00
|   |   |   |   |   |   |--- market_segment_type_Corporate <= 0.50
|   |   |   |   |   |   |   |--- weights: [18.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- market_segment_type_Corporate >  0.50
|   |   |   |   |   |   |   |--- lead_time <= 12.50
|   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  12.50
|   |   |   |   |   |   |   |   |--- weights: [2.00, 1.00] class: 0.0
|   |   |   |   |   |--- lead_time >  63.00
|   |   |   |   |   |   |--- weights: [0.00, 6.00] class: 1.0
|   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |--- lead_time <= 102.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 3.50
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 <= 0.50
|   |   |   |   |   |   |   |   |--- lead_time <= 91.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 129.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [848.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  129.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 131.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  131.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [27.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  91.50
|   |   |   |   |   |   |   |   |   |--- no_of_children <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [43.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_children >  0.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 95.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  95.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 >  0.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 164.79
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [11.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- market_segment_type_Corporate <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- market_segment_type_Corporate >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  164.79
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  3.50
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |--- lead_time >  102.50
|   |   |   |   |   |   |--- lead_time <= 104.50
|   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 67.65
|   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  67.65
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 4.00] class: 1.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  104.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 141.75
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 83.39
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  83.39
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 143.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  143.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 122.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [54.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  122.00
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 7 <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 7 >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  141.75
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |--- lead_time <= 8.50
|   |   |   |   |   |--- lead_time <= 4.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 3.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 157.64
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 <= 0.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 4.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [81.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  4.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 15
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [69.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 >  0.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  157.64
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 158.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  158.50
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 17.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  17.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |--- no_of_weekend_nights >  3.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |--- lead_time >  4.50
|   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 <= 0.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 123.60
|   |   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 13.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 4.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  4.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- arrival_date >  13.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [37.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |   |--- weights: [95.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  123.60
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  6.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 15.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 128.91
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  128.91
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |--- arrival_date >  15.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [42.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  6.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 >  0.50
|   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |--- lead_time >  8.50
|   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |--- avg_price_per_room <= 127.62
|   |   |   |   |   |   |   |--- no_of_weekend_nights <= 2.50
|   |   |   |   |   |   |   |   |--- lead_time <= 43.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [87.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 23
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [128.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  43.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 21
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 21
|   |   |   |   |   |   |   |--- no_of_weekend_nights >  2.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 119.12
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 10.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 10.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  10.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  119.12
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  127.62
|   |   |   |   |   |   |   |--- lead_time <= 142.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 177.15
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 15
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  177.15
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 21
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 100.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [49.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  100.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |--- lead_time >  142.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 142.65
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  142.65
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 179.11
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 11.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  179.11
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 144.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  144.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |--- room_type_reserved_Room_Type 7 <= 0.50
|   |   |   |   |   |   |   |--- weights: [180.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- room_type_reserved_Room_Type 7 >  0.50
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |--- no_of_special_requests >  1.50
|   |   |   |--- lead_time <= 90.50
|   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |--- weights: [2126.00, 0.00] class: 0.0
|   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 4.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 92.42
|   |   |   |   |   |   |   |   |   |--- lead_time <= 54.00
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 91.90
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  91.90
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- lead_time >  54.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 78.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  78.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  92.42
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 107.29
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 28.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [36.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  28.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  107.29
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- weights: [34.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  4.50
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |--- weights: [70.00, 0.00] class: 0.0
|   |   |   |--- lead_time >  90.50
|   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |--- lead_time <= 150.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 4.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  4.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 26.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 5.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  26.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 14.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [8.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  14.00
|   |   |   |   |   |   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- no_of_children <= 0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 157.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 29.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  29.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  157.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 12.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  12.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [7.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_children >  0.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_children <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- no_of_children >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  6.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |--- lead_time >  150.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 103.50
|   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  103.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 5.00] class: 1.0
|   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |--- avg_price_per_room <= 90.42
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 21.50
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 123.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  123.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  21.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 90.12
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  90.12
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- lead_time <= 101.00
|   |   |   |   |   |   |   |   |   |--- weights: [11.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  101.00
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 7.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  7.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 21.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [7.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  21.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |--- avg_price_per_room >  90.42
|   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |--- weights: [11.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 153.15
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 148.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  148.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  153.15
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 26.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 148.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [14.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  148.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- arrival_date >  26.50
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |--- weights: [90.00, 0.00] class: 0.0
|--- lead_time >  151.50
|   |--- avg_price_per_room <= 100.04
|   |   |--- no_of_special_requests <= 0.50
|   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |--- lead_time <= 163.50
|   |   |   |   |   |   |--- lead_time <= 162.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 62.50
|   |   |   |   |   |   |   |   |--- weights: [1.00, 1.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  62.50
|   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  162.50
|   |   |   |   |   |   |   |--- weights: [0.00, 15.00] class: 1.0
|   |   |   |   |   |--- lead_time >  163.50
|   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |--- lead_time <= 173.00
|   |   |   |   |   |   |   |   |--- arrival_date <= 3.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [61.00, 6.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  3.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 70.85
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  70.85
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 9.00] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  173.00
|   |   |   |   |   |   |   |   |--- arrival_month <= 4.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  4.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 17.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  17.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 5.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  5.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9
|   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |--- lead_time <= 283.25
|   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  283.25
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 88.33
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 7.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  88.33
|   |   |   |   |   |   |   |   |   |--- weights: [1.00, 1.00] class: 0.0
|   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |--- avg_price_per_room <= 84.58
|   |   |   |   |   |   |--- lead_time <= 244.00
|   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 166.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  166.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  19.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- weights: [24.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 66.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 64.80
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  64.80
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 7.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 28.57
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  28.57
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  66.50
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 75.75
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  75.75
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |--- lead_time >  244.00
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- weights: [34.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 80.38
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  80.38
|   |   |   |   |   |   |   |   |   |   |--- weights: [11.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- weights: [37.00, 0.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  84.58
|   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 <= 0.50
|   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 1 >  0.50
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Corporate <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Corporate >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 6.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 13.00] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  6.50
|   |   |   |   |   |   |   |   |   |--- weights: [14.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |--- weights: [9.00, 0.00] class: 0.0
|   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |--- avg_price_per_room <= 35.17
|   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |--- lead_time <= 205.00
|   |   |   |   |   |   |   |--- arrival_month <= 6.00
|   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  6.00
|   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  205.00
|   |   |   |   |   |   |   |--- arrival_date <= 19.00
|   |   |   |   |   |   |   |   |--- weights: [0.00, 5.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_date >  19.00
|   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |--- weights: [9.00, 0.00] class: 0.0
|   |   |   |   |--- avg_price_per_room >  35.17
|   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |--- weights: [0.00, 523.00] class: 1.0
|   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |--- lead_time <= 263.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 76.87
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 5.00] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  76.87
|   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  263.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 7.00] class: 1.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 3.50
|   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  3.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 6.00] class: 1.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 58.00] class: 1.0
|   |   |--- no_of_special_requests >  0.50
|   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |--- lead_time <= 180.50
|   |   |   |   |   |--- lead_time <= 159.50
|   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |--- weights: [8.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |--- arrival_date <= 23.50
|   |   |   |   |   |   |   |   |--- lead_time <= 156.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |--- lead_time >  156.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_date >  23.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 4.00] class: 1.0
|   |   |   |   |   |--- lead_time >  159.50
|   |   |   |   |   |   |--- no_of_adults <= 0.50
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |--- no_of_adults >  0.50
|   |   |   |   |   |   |   |--- arrival_date <= 1.50
|   |   |   |   |   |   |   |   |--- lead_time <= 176.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  176.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_date >  1.50
|   |   |   |   |   |   |   |   |--- weights: [48.00, 0.00] class: 0.0
|   |   |   |   |--- lead_time >  180.50
|   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 0.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 125.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- lead_time <= 272.00
|   |   |   |   |   |   |   |   |   |--- lead_time <= 226.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  226.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  272.00
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 73.10
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  73.10
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 23.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 6.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  23.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |   |--- weights: [12.00, 0.00] class: 0.0
|   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |--- avg_price_per_room <= 96.37
|   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |--- lead_time <= 279.75
|   |   |   |   |   |   |   |   |   |--- weights: [15.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  279.75
|   |   |   |   |   |   |   |   |   |--- weights: [2.00, 1.00] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  96.37
|   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |   |--- no_of_week_nights <= 5.50
|   |   |   |   |   |   |--- lead_time <= 284.25
|   |   |   |   |   |   |   |--- arrival_date <= 30.00
|   |   |   |   |   |   |   |   |--- weights: [119.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_date >  30.00
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.00
|   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.00
|   |   |   |   |   |   |   |   |   |--- weights: [2.00, 1.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  284.25
|   |   |   |   |   |   |   |--- arrival_date <= 21.00
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |--- weights: [13.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 58.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  58.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.00, 2.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_date >  21.00
|   |   |   |   |   |   |   |   |--- weights: [1.00, 1.00] class: 0.0
|   |   |   |   |   |--- no_of_week_nights >  5.50
|   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 3.50
|   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 81.12
|   |   |   |   |   |   |   |   |   |--- lead_time <= 153.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 2.00] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  153.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 157.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  157.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  81.12
|   |   |   |   |   |   |   |   |   |--- lead_time <= 231.50
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 14
|   |   |   |   |   |   |   |   |   |--- lead_time >  231.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_children <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9
|   |   |   |   |   |   |   |   |   |   |--- no_of_children >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 224.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 175.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  175.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 10.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  224.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 269.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 176.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  176.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- lead_time >  269.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  3.50
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 5.50
|   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  5.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 6.00] class: 1.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |--- arrival_date <= 14.50
|   |   |   |   |   |   |   |--- arrival_date <= 3.00
|   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_date >  3.00
|   |   |   |   |   |   |   |   |--- lead_time <= 217.50
|   |   |   |   |   |   |   |   |   |--- weights: [8.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  217.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 235.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  235.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_date >  14.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 55.92
|   |   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  55.92
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 80.19
|   |   |   |   |   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 68.32
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  68.32
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  80.19
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 89.75
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  89.75
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.00] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [4.00, 0.00] class: 0.0
|   |--- avg_price_per_room >  100.04
|   |   |--- arrival_month <= 11.50
|   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |--- weights: [0.00, 2108.00] class: 1.0
|   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |--- weights: [31.00, 0.00] class: 0.0
|   |   |--- arrival_month >  11.50
|   |   |   |--- no_of_special_requests <= 0.50
|   |   |   |   |--- weights: [47.00, 0.00] class: 0.0
|   |   |   |--- no_of_special_requests >  0.50
|   |   |   |   |--- arrival_date <= 24.50
|   |   |   |   |   |--- weights: [5.00, 0.00] class: 0.0
|   |   |   |   |--- arrival_date >  24.50
|   |   |   |   |   |--- room_type_reserved_Room_Type 1 <= 0.50
|   |   |   |   |   |   |--- lead_time <= 172.50
|   |   |   |   |   |   |   |--- no_of_children <= 1.00
|   |   |   |   |   |   |   |   |--- weights: [2.00, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_children >  1.00
|   |   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |--- lead_time >  172.50
|   |   |   |   |   |   |   |--- weights: [0.00, 13.00] class: 1.0
|   |   |   |   |   |--- room_type_reserved_Room_Type 1 >  0.50
|   |   |   |   |   |   |--- avg_price_per_room <= 113.47
|   |   |   |   |   |   |   |--- weights: [0.00, 1.00] class: 1.0
|   |   |   |   |   |   |--- avg_price_per_room >  113.47
|   |   |   |   |   |   |   |--- weights: [3.00, 0.00] class: 0.0


# importance of features in the tree building ( The importance of a feature is computed as the
# (normalized) total reduction of the criterion brought by that feature. It is also known as the Gini importance )

print(
    pd.DataFrame(
        dTree.feature_importances_, columns=["Imp"], index=X_train.columns
    ).sort_values(by="Imp", ascending=False)
)

                                           Imp
lead_time                             0.350426
avg_price_per_room                    0.169167
market_segment_type_Online            0.093218
arrival_date                          0.085588
no_of_special_requests                0.067350
arrival_month                         0.063954
no_of_week_nights                     0.044595
no_of_weekend_nights                  0.041870
no_of_adults                          0.027230
type_of_meal_plan                     0.014130
arrival_year                          0.012097
required_car_parking_space            0.006614
no_of_children                        0.005075
room_type_reserved_Room_Type 4        0.004837
room_type_reserved_Room_Type 1        0.004795
market_segment_type_Offline           0.002930
room_type_reserved_Room_Type 2        0.001758
room_type_reserved_Room_Type 5        0.000983
market_segment_type_Corporate         0.000784
room_type_reserved_Room_Type 7        0.000773
repeated_guest                        0.000638
market_segment_type_Aviation          0.000412
room_type_reserved_Room_Type 6        0.000406
no_of_previous_bookings_not_canceled  0.000212
no_of_previous_cancellations          0.000091
market_segment_type_Complementary     0.000054
room_type_reserved_Room_Type 3        0.000013


importances = dTree.feature_importances_
indices = np.argsort(importances)

plt.figure(figsize=(12, 12))
plt.title("Feature Importances")
plt.barh(range(len(indices)), importances[indices], color="violet", align="center")
plt.yticks(range(len(indices)), [feature_names[i] for i in indices])
plt.xlabel("Relative Importance")
plt.show()


# Choose the type of classifier.
estimator = DecisionTreeClassifier(random_state=1, class_weight="balanced")

# Grid of parameters to choose from
parameters = {
    "max_depth": [5, 10, 15, None],
    "max_leaf_nodes": [50, 75, 150, 250],
    "splitter": ["best", "random"],
    "criterion": ["entropy", "gini"],
    "min_impurity_decrease": [0.00001, 0.0001, 0.01],
}

# Type of scoring used to compare parameter combinations
acc_scorer = make_scorer(f1_score)

# Run the grid search
grid_obj = GridSearchCV(estimator, parameters, scoring=acc_scorer, cv=5)
grid_obj = grid_obj.fit(X_train, y_train)

# Set the clf to the best combination of parameters
estimator = grid_obj.best_estimator_

# Fit the best algorithm to the data.
estimator.fit(X_train, y_train)

DecisionTreeClassifier(class_weight='balanced', criterion='entropy',
                       max_leaf_nodes=250, min_impurity_decrease=1e-05,
                       random_state=1)


confusion_matrix_sklearn(estimator, X_train, y_train)


decision_tree_tune_perf_train = model_performance_classification_sklearn(
    estimator, X_train, y_train
)
decision_tree_tune_perf_train


confusion_matrix_sklearn(estimator, X_test, y_test)


decision_tree_tune_perf_test = model_performance_classification_sklearn(
    estimator, X_test, y_test
)
decision_tree_tune_perf_test


feature_names = list(X.columns)

plt.figure(figsize=(20, 30))
tree.plot_tree(
    estimator,
    feature_names=feature_names,
    filled=True,
    fontsize=9,
    node_ids=True,
    class_names=True,
)
plt.show()


# Text report showing the rules of a decision tree -

print(tree.export_text(estimator, feature_names=feature_names, show_weights=True))

|--- lead_time <= 151.50
|   |--- no_of_special_requests <= 0.50
|   |   |--- market_segment_type_Online <= 0.50
|   |   |   |--- lead_time <= 74.50
|   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |   |--- repeated_guest <= 0.50
|   |   |   |   |   |   |   |   |--- market_segment_type_Complementary <= 0.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 30.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [91.70, 9.11] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  30.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [9.69, 7.59] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  11.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |--- market_segment_type_Complementary >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [39.51, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- repeated_guest >  0.50
|   |   |   |   |   |   |   |   |--- lead_time <= 44.50
|   |   |   |   |   |   |   |   |   |--- weights: [106.61, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  44.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.24, 3.04] class: 1.0
|   |   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 178.44
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |--- weights: [697.09, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 48.17
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 46.58
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [5.22, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  46.58
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 10.63] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  48.17
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [35.79, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [148.36, 36.43] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  178.44
|   |   |   |   |   |   |   |   |--- lead_time <= 22.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.98, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  22.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 37.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 24.29] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  37.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.49, 0.00] class: 0.0
|   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |--- arrival_month <= 6.50
|   |   |   |   |   |   |   |   |--- market_segment_type_Corporate <= 0.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [5.96, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 102.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  102.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 68.32] class: 1.0
|   |   |   |   |   |   |   |   |--- market_segment_type_Corporate >  0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 120.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [14.91, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  120.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.04] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  6.50
|   |   |   |   |   |   |   |   |--- weights: [26.84, 4.55] class: 0.0
|   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |--- lead_time <= 59.50
|   |   |   |   |   |   |   |   |--- weights: [175.95, 22.77] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  59.50
|   |   |   |   |   |   |   |   |--- lead_time <= 63.00
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.98, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 12.14] class: 1.0
|   |   |   |   |   |   |   |   |--- lead_time >  63.00
|   |   |   |   |   |   |   |   |   |--- weights: [18.64, 3.04] class: 0.0
|   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |--- repeated_guest <= 0.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 10.50
|   |   |   |   |   |   |   |   |   |--- weights: [84.25, 9.11] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_month >  10.50
|   |   |   |   |   |   |   |   |   |--- weights: [59.64, 24.29] class: 0.0
|   |   |   |   |   |   |   |--- repeated_guest >  0.50
|   |   |   |   |   |   |   |   |--- weights: [55.17, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |--- weights: [85.74, 0.00] class: 0.0
|   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |--- weights: [405.58, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 67.25
|   |   |   |   |   |   |   |   |--- weights: [87.98, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  67.25
|   |   |   |   |   |   |   |   |--- weights: [225.16, 18.22] class: 0.0
|   |   |   |--- lead_time >  74.50
|   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |--- weights: [73.06, 0.00] class: 0.0
|   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |--- lead_time <= 99.50
|   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |--- lead_time <= 85.50
|   |   |   |   |   |   |   |   |   |--- weights: [61.88, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  85.50
|   |   |   |   |   |   |   |   |   |--- weights: [99.16, 19.74] class: 0.0
|   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 99.98
|   |   |   |   |   |   |   |   |   |--- lead_time <= 98.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 61.88
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [17.89, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  61.88
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- lead_time >  98.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 13.66] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  99.98
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  9.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 68.32] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |--- lead_time >  99.50
|   |   |   |   |   |   |   |--- lead_time <= 116.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 86.53] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [25.35, 92.61] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Corporate <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 109.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  109.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Corporate >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 39.47] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  116.50
|   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 122.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [64.86, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  122.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.04] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [14.17, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 74.12
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [9.69, 10.63] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  74.12
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |--- avg_price_per_room <= 165.11
|   |   |   |   |   |   |--- weights: [99.16, 0.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  165.11
|   |   |   |   |   |   |--- weights: [0.75, 1.52] class: 1.0
|   |   |--- market_segment_type_Online >  0.50
|   |   |   |--- lead_time <= 13.50
|   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |--- lead_time <= 3.50
|   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |--- weights: [49.95, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 178.78
|   |   |   |   |   |   |   |   |--- arrival_month <= 5.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 77.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [17.89, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  77.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [105.87, 51.62] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 23.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.20, 4.55] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  23.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 22.77] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  5.50
|   |   |   |   |   |   |   |   |   |--- weights: [225.90, 39.47] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  178.78
|   |   |   |   |   |   |   |   |--- weights: [14.17, 25.81] class: 1.0
|   |   |   |   |   |--- lead_time >  3.50
|   |   |   |   |   |   |--- avg_price_per_room <= 99.38
|   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |--- weights: [44.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 69.37
|   |   |   |   |   |   |   |   |   |--- weights: [20.13, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  69.37
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [87.23, 62.24] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 10.63] class: 1.0
|   |   |   |   |   |   |--- avg_price_per_room >  99.38
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- weights: [23.86, 4.55] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |   |--- weights: [57.41, 229.24] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 14.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [9.69, 36.43] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  14.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [20.13, 10.63] class: 0.0
|   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |--- weights: [123.02, 0.00] class: 0.0
|   |   |   |--- lead_time >  13.50
|   |   |   |   |--- avg_price_per_room <= 105.27
|   |   |   |   |   |--- avg_price_per_room <= 59.43
|   |   |   |   |   |   |--- avg_price_per_room <= 28.50
|   |   |   |   |   |   |   |--- weights: [25.35, 0.00] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  28.50
|   |   |   |   |   |   |   |--- weights: [42.50, 22.77] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  59.43
|   |   |   |   |   |   |--- lead_time <= 25.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [21.62, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.49, 3.04] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [20.88, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [43.99, 126.00] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- weights: [40.26, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  25.50
|   |   |   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |--- weights: [99.16, 487.32] class: 1.0
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 53.13] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 3.04] class: 1.0
|   |   |   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |   |   |--- weights: [15.66, 0.00] class: 0.0
|   |   |   |   |--- avg_price_per_room >  105.27
|   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |--- arrival_month <= 10.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 173.12
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 71.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [14.17, 6.07] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  71.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 15.18] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 24.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  24.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [80.52, 343.09] class: 1.0
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 >  0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 4.55] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 6.07] class: 1.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  173.12
|   |   |   |   |   |   |   |   |--- no_of_children <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [13.42, 89.57] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_children >  1.50
|   |   |   |   |   |   |   |   |   |--- weights: [3.73, 154.85] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  10.50
|   |   |   |   |   |   |   |--- lead_time <= 22.50
|   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.75, 6.07] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |--- weights: [16.40, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  22.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 168.06
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 147.75
|   |   |   |   |   |   |   |   |   |   |--- weights: [20.13, 62.24] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  147.75
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 22.77] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  168.06
|   |   |   |   |   |   |   |   |   |--- weights: [11.93, 6.07] class: 0.0
|   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |--- no_of_week_nights <= 5.50
|   |   |   |   |   |   |   |--- weights: [29.08, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_week_nights >  5.50
|   |   |   |   |   |   |   |--- weights: [0.00, 1.52] class: 1.0
|   |--- no_of_special_requests >  0.50
|   |   |--- no_of_special_requests <= 1.50
|   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |--- lead_time <= 71.50
|   |   |   |   |   |--- avg_price_per_room <= 94.50
|   |   |   |   |   |   |--- weights: [474.92, 0.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  94.50
|   |   |   |   |   |   |--- market_segment_type_Corporate <= 0.50
|   |   |   |   |   |   |   |--- weights: [97.67, 0.00] class: 0.0
|   |   |   |   |   |   |--- market_segment_type_Corporate >  0.50
|   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |--- weights: [29.08, 1.52] class: 0.0
|   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |--- weights: [3.73, 6.07] class: 1.0
|   |   |   |   |--- lead_time >  71.50
|   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |--- weights: [0.00, 9.11] class: 1.0
|   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |--- lead_time <= 91.50
|   |   |   |   |   |   |   |--- weights: [73.81, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  91.50
|   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |--- weights: [37.28, 19.74] class: 0.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 8.50
|   |   |   |   |   |   |   |   |   |--- weights: [17.89, 4.55] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  8.50
|   |   |   |   |   |   |   |   |   |--- weights: [55.17, 0.00] class: 0.0
|   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |--- lead_time <= 6.50
|   |   |   |   |   |--- avg_price_per_room <= 157.64
|   |   |   |   |   |   |--- weights: [556.18, 48.58] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  157.64
|   |   |   |   |   |   |--- arrival_date <= 18.50
|   |   |   |   |   |   |   |--- arrival_date <= 16.50
|   |   |   |   |   |   |   |   |--- weights: [38.02, 12.14] class: 0.0
|   |   |   |   |   |   |   |--- arrival_date >  16.50
|   |   |   |   |   |   |   |   |--- weights: [1.49, 7.59] class: 1.0
|   |   |   |   |   |   |--- arrival_date >  18.50
|   |   |   |   |   |   |   |--- weights: [39.51, 3.04] class: 0.0
|   |   |   |   |--- lead_time >  6.50
|   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |--- weights: [78.28, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 118.55
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 66.30
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  66.30
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  2.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 27.33] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  118.55
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [174.46, 159.40] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [258.71, 344.61] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- lead_time <= 100.00
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 3.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [242.30, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  3.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [1.49, 3.04] class: 1.0
|   |   |   |   |   |   |   |   |--- lead_time >  100.00
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 92.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [13.42, 19.74] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  92.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 30.36] class: 1.0
|   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 3.00
|   |   |   |   |   |   |   |--- weights: [140.16, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  3.00
|   |   |   |   |   |   |   |--- weights: [0.00, 1.52] class: 1.0
|   |   |--- no_of_special_requests >  1.50
|   |   |   |--- lead_time <= 90.50
|   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |--- weights: [1585.04, 0.00] class: 0.0
|   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |--- lead_time <= 4.50
|   |   |   |   |   |   |   |--- weights: [22.37, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  4.50
|   |   |   |   |   |   |   |--- weights: [158.06, 57.69] class: 0.0
|   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |--- weights: [52.19, 0.00] class: 0.0
|   |   |   |--- lead_time >  90.50
|   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |--- lead_time <= 150.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- weights: [8.20, 12.14] class: 1.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- no_of_children <= 0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 157.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [140.91, 13.66] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  157.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [6.71, 6.07] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_children >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [27.59, 16.70] class: 0.0
|   |   |   |   |   |   |--- lead_time >  150.50
|   |   |   |   |   |   |   |--- weights: [1.49, 7.59] class: 1.0
|   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |--- weights: [106.61, 106.27] class: 0.0
|   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |--- weights: [67.10, 0.00] class: 0.0
|--- lead_time >  151.50
|   |--- avg_price_per_room <= 100.04
|   |   |--- no_of_special_requests <= 0.50
|   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |--- lead_time <= 163.50
|   |   |   |   |   |   |--- avg_price_per_room <= 85.50
|   |   |   |   |   |   |   |--- weights: [3.73, 1.52] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  85.50
|   |   |   |   |   |   |   |--- weights: [0.00, 22.77] class: 1.0
|   |   |   |   |   |--- lead_time >  163.50
|   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |--- lead_time <= 173.00
|   |   |   |   |   |   |   |   |--- arrival_date <= 3.50
|   |   |   |   |   |   |   |   |   |--- weights: [46.97, 9.11] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  3.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 13.66] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  173.00
|   |   |   |   |   |   |   |   |--- arrival_month <= 5.50
|   |   |   |   |   |   |   |   |   |--- weights: [6.71, 7.59] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  5.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 231.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [79.03, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  231.00
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |--- weights: [2.24, 12.14] class: 1.0
|   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |--- avg_price_per_room <= 88.50
|   |   |   |   |   |   |   |--- lead_time <= 269.50
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 168.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [8.95, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  168.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [4.47, 89.57] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 83.72
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  83.72
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 34.92] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  269.50
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- weights: [16.40, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [8.95, 214.05] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 74.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  74.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |--- avg_price_per_room >  88.50
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |--- no_of_adults <= 2.50
|   |   |   |   |   |   |   |   |   |--- weights: [7.46, 458.47] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_adults >  2.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.98, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |--- weights: [4.47, 0.00] class: 0.0
|   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |--- weights: [53.68, 0.00] class: 0.0
|   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |--- avg_price_per_room <= 35.17
|   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |--- weights: [2.24, 9.11] class: 1.0
|   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |--- weights: [6.71, 0.00] class: 0.0
|   |   |   |   |--- avg_price_per_room >  35.17
|   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |--- weights: [0.00, 793.97] class: 1.0
|   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |--- weights: [3.73, 115.38] class: 1.0
|   |   |--- no_of_special_requests >  0.50
|   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |--- lead_time <= 180.50
|   |   |   |   |   |--- weights: [44.73, 12.14] class: 0.0
|   |   |   |   |--- lead_time >  180.50
|   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |   |   |   |--- weights: [12.67, 6.07] class: 0.0
|   |   |   |   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 44.12
|   |   |   |   |   |   |   |   |   |--- weights: [1.49, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  44.12
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 189.76] class: 1.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- weights: [5.96, 16.70] class: 1.0
|   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |--- weights: [8.95, 0.00] class: 0.0
|   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |   |--- arrival_date <= 13.50
|   |   |   |   |   |   |--- weights: [67.85, 0.00] class: 0.0
|   |   |   |   |   |--- arrival_date >  13.50
|   |   |   |   |   |   |--- weights: [44.73, 7.59] class: 0.0
|   |   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |--- avg_price_per_room <= 76.48
|   |   |   |   |   |   |   |--- weights: [46.97, 4.55] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  76.48
|   |   |   |   |   |   |   |--- weights: [184.15, 106.27] class: 0.0
|   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |--- weights: [19.38, 34.92] class: 1.0
|   |--- avg_price_per_room >  100.04
|   |   |--- arrival_month <= 11.50
|   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |--- weights: [0.00, 3200.19] class: 1.0
|   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |--- weights: [23.11, 0.00] class: 0.0
|   |   |--- arrival_month >  11.50
|   |   |   |--- no_of_special_requests <= 0.50
|   |   |   |   |--- weights: [35.04, 0.00] class: 0.0
|   |   |   |--- no_of_special_requests >  0.50
|   |   |   |   |--- arrival_date <= 24.50
|   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |--- arrival_date >  24.50
|   |   |   |   |   |--- weights: [3.73, 22.77] class: 1.0


# importance of features in the tree building ( The importance of a feature is computed as the
# (normalized) total reduction of the criterion brought by that feature. It is also known as the Gini importance )

print(
    pd.DataFrame(
        estimator.feature_importances_, columns=["Imp"], index=X_train.columns
    ).sort_values(by="Imp", ascending=False)
)

                                           Imp
lead_time                             0.355371
market_segment_type_Online            0.138466
avg_price_per_room                    0.131435
no_of_special_requests                0.126682
arrival_month                         0.085446
no_of_weekend_nights                  0.038676
no_of_adults                          0.029807
no_of_week_nights                     0.023794
arrival_date                          0.020978
arrival_year                          0.013810
required_car_parking_space            0.011676
type_of_meal_plan                     0.006148
market_segment_type_Corporate         0.005068
market_segment_type_Offline           0.004843
repeated_guest                        0.003012
room_type_reserved_Room_Type 4        0.001511
market_segment_type_Complementary     0.001281
no_of_children                        0.001206
room_type_reserved_Room_Type 5        0.000792
room_type_reserved_Room_Type 7        0.000000
market_segment_type_Aviation          0.000000
room_type_reserved_Room_Type 3        0.000000
room_type_reserved_Room_Type 6        0.000000
room_type_reserved_Room_Type 2        0.000000
no_of_previous_bookings_not_canceled  0.000000
no_of_previous_cancellations          0.000000
room_type_reserved_Room_Type 1        0.000000


importances = estimator.feature_importances_
indices = np.argsort(importances)

plt.figure(figsize=(12, 12))
plt.title("Feature Importances")
plt.barh(range(len(indices)), importances[indices], color="violet", align="center")
plt.yticks(range(len(indices)), [feature_names[i] for i in indices])
plt.xlabel("Relative Importance")
plt.show()


clf = DecisionTreeClassifier(random_state=1, class_weight="balanced")
path = clf.cost_complexity_pruning_path(X_train, y_train)
ccp_alphas, impurities = abs(path.ccp_alphas), path.impurities


pd.DataFrame(path)


fig, ax = plt.subplots(figsize=(10, 5))
ax.plot(ccp_alphas[:-1], impurities[:-1], marker="o", drawstyle="steps-post")
ax.set_xlabel("effective alpha")
ax.set_ylabel("total impurity of leaves")
ax.set_title("Total Impurity vs effective alpha for training set")
plt.show()


clfs = []
for ccp_alpha in ccp_alphas:
    clf = DecisionTreeClassifier(
        random_state=1, ccp_alpha=ccp_alpha, class_weight="balanced"
    )
    clf.fit(X_train, y_train)
    clfs.append(clf)
print(
    "Number of nodes in the last tree is: {} with ccp_alpha: {}".format(
        clfs[-1].tree_.node_count, ccp_alphas[-1]
    )
)

Number of nodes in the last tree is: 1 with ccp_alpha: 0.08117914389136949


clfs = clfs[:-1]
ccp_alphas = ccp_alphas[:-1]

node_counts = [clf.tree_.node_count for clf in clfs]
depth = [clf.tree_.max_depth for clf in clfs]
fig, ax = plt.subplots(2, 1, figsize=(10, 7))
ax[0].plot(ccp_alphas, node_counts, marker="o", drawstyle="steps-post")
ax[0].set_xlabel("alpha")
ax[0].set_ylabel("number of nodes")
ax[0].set_title("Number of nodes vs alpha")
ax[1].plot(ccp_alphas, depth, marker="o", drawstyle="steps-post")
ax[1].set_xlabel("alpha")
ax[1].set_ylabel("depth of tree")
ax[1].set_title("Depth vs alpha")
fig.tight_layout()


f1_train = []
for clf in clfs:
    pred_train = clf.predict(X_train)
    values_train = f1_score(y_train, pred_train)
    f1_train.append(values_train)

f1_test = []
for clf in clfs:
    pred_test = clf.predict(X_test)
    values_test = f1_score(y_test, pred_test)
    f1_test.append(values_test)


fig, ax = plt.subplots(figsize=(15, 5))
ax.set_xlabel("alpha")
ax.set_ylabel("F1 Score")
ax.set_title("F1 Score vs alpha for training and testing sets")
ax.plot(ccp_alphas, f1_train, marker="o", label="train", drawstyle="steps-post")
ax.plot(ccp_alphas, f1_test, marker="o", label="test", drawstyle="steps-post")
ax.legend()
plt.show()


index_best_model = np.argmax(f1_test)
best_model = clfs[index_best_model]
print(best_model)

DecisionTreeClassifier(ccp_alpha=0.0001229122417153721, class_weight='balanced',
                       random_state=1)


confusion_matrix_sklearn(best_model, X_train, y_train)


decision_tree_post_perf_train = model_performance_classification_sklearn(
    best_model, X_train, y_train
)
decision_tree_post_perf_train


confusion_matrix_sklearn(best_model, X_test, y_test)


decision_tree_post_perf_test = model_performance_classification_sklearn(
    best_model, X_test, y_test
)
decision_tree_post_perf_test


plt.figure(figsize=(20, 10))

out = tree.plot_tree(
    best_model,
    feature_names=feature_names,
    filled=True,
    fontsize=9,
    node_ids=False,
    class_names=None,
)
for o in out:
    arrow = o.arrow_patch
    if arrow is not None:
        arrow.set_edgecolor("black")
        arrow.set_linewidth(1)
plt.show()


# Text report showing the rules of a decision tree -

print(tree.export_text(best_model, feature_names=feature_names, show_weights=True))

|--- lead_time <= 151.50
|   |--- no_of_special_requests <= 0.50
|   |   |--- market_segment_type_Online <= 0.50
|   |   |   |--- lead_time <= 90.50
|   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |--- avg_price_per_room <= 179.47
|   |   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |   |--- lead_time <= 16.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 68.50
|   |   |   |   |   |   |   |   |   |--- weights: [207.26, 10.63] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  68.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 29.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5
|   |   |   |   |   |   |   |   |   |--- arrival_date >  29.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 7.59] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  16.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 135.00
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_previous_bookings_not_canceled <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- no_of_previous_bookings_not_canceled >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [21.62, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  135.00
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 12.14] class: 1.0
|   |   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |   |--- weights: [1197.36, 0.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  179.47
|   |   |   |   |   |   |--- weights: [2.98, 25.81] class: 1.0
|   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |--- lead_time <= 68.50
|   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 63.29
|   |   |   |   |   |   |   |   |--- arrival_date <= 20.50
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 3.04] class: 1.0
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [41.75, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  20.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 59.75
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 23.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.49, 12.14] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  23.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [14.91, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  59.75
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 44.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 59.21] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  44.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  63.29
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 3.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 59.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- lead_time >  59.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 5.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  5.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [20.13, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  3.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.75, 15.18] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |--- market_segment_type_Aviation <= 0.50
|   |   |   |   |   |   |   |   |--- weights: [401.85, 21.25] class: 0.0
|   |   |   |   |   |   |   |--- market_segment_type_Aviation >  0.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 7.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.75, 4.55] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_date >  7.50
|   |   |   |   |   |   |   |   |   |--- weights: [10.44, 1.52] class: 0.0
|   |   |   |   |   |--- lead_time >  68.50
|   |   |   |   |   |   |--- avg_price_per_room <= 99.98
|   |   |   |   |   |   |   |--- arrival_month <= 3.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 62.50
|   |   |   |   |   |   |   |   |   |--- weights: [15.66, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  62.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 80.38
|   |   |   |   |   |   |   |   |   |   |--- weights: [8.20, 25.81] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  80.38
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  3.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |   |--- weights: [55.17, 3.04] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 73.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 4.55] class: 1.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  73.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [21.62, 4.55] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  99.98
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- weights: [8.95, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 132.43
|   |   |   |   |   |   |   |   |   |--- weights: [9.69, 122.97] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  132.43
|   |   |   |   |   |   |   |   |   |--- weights: [6.71, 0.00] class: 0.0
|   |   |   |--- lead_time >  90.50
|   |   |   |   |--- lead_time <= 117.50
|   |   |   |   |   |--- avg_price_per_room <= 93.58
|   |   |   |   |   |   |--- avg_price_per_room <= 75.07
|   |   |   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 58.75
|   |   |   |   |   |   |   |   |   |--- weights: [5.96, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  58.75
|   |   |   |   |   |   |   |   |   |--- no_of_previous_cancellations <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 4.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 118.41] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  4.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- no_of_previous_cancellations >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [4.47, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 11.50
|   |   |   |   |   |   |   |   |   |--- weights: [31.31, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  11.50
|   |   |   |   |   |   |   |   |   |--- weights: [29.08, 15.18] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  75.07
|   |   |   |   |   |   |   |--- arrival_month <= 3.50
|   |   |   |   |   |   |   |   |--- weights: [59.64, 3.04] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  3.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 4.50
|   |   |   |   |   |   |   |   |   |--- weights: [1.49, 16.70] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  4.50
|   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 86.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 16.70] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  86.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.95, 3.04] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 22.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [44.73, 4.55] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  22.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |--- avg_price_per_room >  93.58
|   |   |   |   |   |   |--- arrival_date <= 11.50
|   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |--- weights: [16.40, 39.47] class: 1.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |--- weights: [20.13, 6.07] class: 0.0
|   |   |   |   |   |   |--- arrival_date >  11.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 102.09
|   |   |   |   |   |   |   |   |--- weights: [5.22, 144.22] class: 1.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  102.09
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 109.50
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 16.70] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [33.55, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  109.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 124.25
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.98, 75.91] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  124.25
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 3.04] class: 0.0
|   |   |   |   |--- lead_time >  117.50
|   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |--- arrival_date <= 7.50
|   |   |   |   |   |   |   |--- weights: [38.02, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_date >  7.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 93.58
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 65.38
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 4.55] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  65.38
|   |   |   |   |   |   |   |   |   |--- weights: [24.60, 3.04] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  93.58
|   |   |   |   |   |   |   |   |--- arrival_date <= 28.00
|   |   |   |   |   |   |   |   |   |--- weights: [14.91, 72.87] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_date >  28.00
|   |   |   |   |   |   |   |   |   |--- weights: [9.69, 1.52] class: 0.0
|   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |--- weights: [84.25, 0.00] class: 0.0
|   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |--- lead_time <= 125.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 90.85
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 87.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [13.42, 13.66] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  87.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 15.18] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  90.85
|   |   |   |   |   |   |   |   |   |--- weights: [10.44, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  125.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |--- weights: [58.15, 18.22] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |--- weights: [61.88, 1.52] class: 0.0
|   |   |--- market_segment_type_Online >  0.50
|   |   |   |--- lead_time <= 13.50
|   |   |   |   |--- avg_price_per_room <= 99.44
|   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |--- weights: [92.45, 0.00] class: 0.0
|   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 70.05
|   |   |   |   |   |   |   |   |   |--- weights: [31.31, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  70.05
|   |   |   |   |   |   |   |   |   |--- lead_time <= 5.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [38.77, 1.52] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- lead_time >  5.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.71, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [34.30, 40.99] class: 1.0
|   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 19.74] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_adults >  1.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 2.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 74.21
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 3.04] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  74.21
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [9.69, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  2.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [4.47, 10.63] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |--- weights: [155.07, 6.07] class: 0.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |--- weights: [3.73, 10.63] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |--- weights: [7.46, 0.00] class: 0.0
|   |   |   |   |--- avg_price_per_room >  99.44
|   |   |   |   |   |--- lead_time <= 3.50
|   |   |   |   |   |   |--- avg_price_per_room <= 178.78
|   |   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 5.50
|   |   |   |   |   |   |   |   |   |--- weights: [58.15, 30.36] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_month >  5.50
|   |   |   |   |   |   |   |   |   |--- weights: [145.38, 22.77] class: 0.0
|   |   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 6.07] class: 1.0
|   |   |   |   |   |   |--- avg_price_per_room >  178.78
|   |   |   |   |   |   |   |--- weights: [16.40, 25.81] class: 1.0
|   |   |   |   |   |--- lead_time >  3.50
|   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 119.25
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 118.50
|   |   |   |   |   |   |   |   |   |--- weights: [18.64, 59.21] class: 1.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  118.50
|   |   |   |   |   |   |   |   |   |--- weights: [8.20, 1.52] class: 0.0
|   |   |   |   |   |   |   |--- avg_price_per_room >  119.25
|   |   |   |   |   |   |   |   |--- weights: [34.30, 171.55] class: 1.0
|   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- weights: [26.09, 1.52] class: 0.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 14.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [9.69, 36.43] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  14.00
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [8.95, 10.63] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |--- weights: [15.66, 0.00] class: 0.0
|   |   |   |--- lead_time >  13.50
|   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |--- avg_price_per_room <= 71.92
|   |   |   |   |   |   |--- avg_price_per_room <= 59.43
|   |   |   |   |   |   |   |--- lead_time <= 84.50
|   |   |   |   |   |   |   |   |--- weights: [50.70, 7.59] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  84.50
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 131.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 15.18] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  131.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  27.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- weights: [10.44, 0.00] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  59.43
|   |   |   |   |   |   |   |--- lead_time <= 25.50
|   |   |   |   |   |   |   |   |--- weights: [20.88, 6.07] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  25.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 71.34
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 3.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 68.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [15.66, 78.94] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  68.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- arrival_month >  3.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 102.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  102.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [12.67, 3.04] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  71.34
|   |   |   |   |   |   |   |   |   |--- weights: [11.18, 0.00] class: 0.0
|   |   |   |   |   |--- avg_price_per_room >  71.92
|   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |--- lead_time <= 65.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 120.45
|   |   |   |   |   |   |   |   |   |--- weights: [79.77, 9.11] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  120.45
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 12.14] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  65.50
|   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [16.40, 47.06] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 63.76] class: 1.0
|   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |--- avg_price_per_room <= 104.31
|   |   |   |   |   |   |   |   |--- lead_time <= 25.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [16.40, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [38.77, 118.41] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [23.11, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- lead_time >  25.50
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [73.81, 411.41] class: 1.0
|   |   |   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [39.51, 185.21] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |--- avg_price_per_room >  104.31
|   |   |   |   |   |   |   |   |--- arrival_month <= 10.50
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 144.76
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  144.76
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [71.57, 669.49] class: 1.0
|   |   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 5 >  0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 22.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 6.07] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  22.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 9.11] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  10.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 168.06
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 22.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  22.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [17.15, 83.50] class: 1.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  168.06
|   |   |   |   |   |   |   |   |   |   |--- weights: [12.67, 6.07] class: 0.0
|   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |--- weights: [48.46, 1.52] class: 0.0
|   |--- no_of_special_requests >  0.50
|   |   |--- no_of_special_requests <= 1.50
|   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |--- lead_time <= 102.50
|   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |--- lead_time <= 63.00
|   |   |   |   |   |   |   |--- weights: [15.66, 1.52] class: 0.0
|   |   |   |   |   |   |--- lead_time >  63.00
|   |   |   |   |   |   |   |--- weights: [0.00, 7.59] class: 1.0
|   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |--- weights: [697.09, 9.11] class: 0.0
|   |   |   |   |--- lead_time >  102.50
|   |   |   |   |   |--- no_of_week_nights <= 2.50
|   |   |   |   |   |   |--- lead_time <= 105.00
|   |   |   |   |   |   |   |--- weights: [0.75, 6.07] class: 1.0
|   |   |   |   |   |   |--- lead_time >  105.00
|   |   |   |   |   |   |   |--- weights: [31.31, 13.66] class: 0.0
|   |   |   |   |   |--- no_of_week_nights >  2.50
|   |   |   |   |   |   |--- weights: [44.73, 3.04] class: 0.0
|   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |--- lead_time <= 8.50
|   |   |   |   |   |--- lead_time <= 4.50
|   |   |   |   |   |   |--- no_of_weekend_nights <= 3.50
|   |   |   |   |   |   |   |--- weights: [497.28, 40.99] class: 0.0
|   |   |   |   |   |   |--- no_of_weekend_nights >  3.50
|   |   |   |   |   |   |   |--- weights: [0.75, 3.04] class: 1.0
|   |   |   |   |   |--- lead_time >  4.50
|   |   |   |   |   |   |--- arrival_date <= 13.50
|   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |--- weights: [58.90, 36.43] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |--- weights: [33.55, 1.52] class: 0.0
|   |   |   |   |   |   |--- arrival_date >  13.50
|   |   |   |   |   |   |   |--- type_of_meal_plan <= 0.00
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 126.33
|   |   |   |   |   |   |   |   |   |--- weights: [32.80, 3.04] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  126.33
|   |   |   |   |   |   |   |   |   |--- weights: [9.69, 13.66] class: 1.0
|   |   |   |   |   |   |   |--- type_of_meal_plan >  0.00
|   |   |   |   |   |   |   |   |--- weights: [123.76, 9.11] class: 0.0
|   |   |   |   |--- lead_time >  8.50
|   |   |   |   |   |--- required_car_parking_space <= 0.50
|   |   |   |   |   |   |--- avg_price_per_room <= 118.55
|   |   |   |   |   |   |   |--- lead_time <= 61.50
|   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [70.08, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  1.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |--- weights: [126.74, 1.52] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  61.50
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 7.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [4.47, 57.69] class: 1.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  7.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 66.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [5.22, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  66.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [37.28, 54.65] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 71.93
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [54.43, 3.04] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  71.93
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10
|   |   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6
|   |   |   |   |   |   |--- avg_price_per_room >  118.55
|   |   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |   |--- arrival_date <= 19.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 177.15
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 118.98
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  118.98
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  177.15
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 7.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.71, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  7.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [12.67, 24.29] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_date >  19.50
|   |   |   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 121.20
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [18.64, 6.07] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  121.20
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
|   |   |   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 55.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  55.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [11.93, 10.63] class: 0.0
|   |   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [37.28, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 119.20
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [9.69, 28.84] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  119.20
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12
|   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 100.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [49.95, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  100.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.75, 18.22] class: 1.0
|   |   |   |   |   |--- required_car_parking_space >  0.50
|   |   |   |   |   |   |--- weights: [134.20, 1.52] class: 0.0
|   |   |--- no_of_special_requests >  1.50
|   |   |   |--- lead_time <= 90.50
|   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |--- weights: [1585.04, 0.00] class: 0.0
|   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |--- lead_time <= 6.50
|   |   |   |   |   |   |   |--- weights: [32.06, 1.52] class: 0.0
|   |   |   |   |   |   |--- lead_time >  6.50
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |--- weights: [103.63, 50.10] class: 0.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |--- weights: [44.73, 6.07] class: 0.0
|   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |--- weights: [52.19, 0.00] class: 0.0
|   |   |   |--- lead_time >  90.50
|   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |--- lead_time <= 150.50
|   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |--- weights: [8.20, 12.14] class: 1.0
|   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |--- no_of_children <= 0.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 157.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [140.91, 13.66] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  157.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_date <= 12.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.49, 6.07] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_date >  12.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [5.22, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_children >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [27.59, 16.70] class: 0.0
|   |   |   |   |   |   |--- lead_time >  150.50
|   |   |   |   |   |   |   |--- weights: [1.49, 7.59] class: 1.0
|   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |--- avg_price_per_room <= 153.15
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 <= 0.50
|   |   |   |   |   |   |   |   |--- avg_price_per_room <= 71.12
|   |   |   |   |   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- avg_price_per_room >  71.12
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 90.42
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [12.67, 7.59] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  90.42
|   |   |   |   |   |   |   |   |   |   |--- weights: [64.12, 60.72] class: 0.0
|   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 2 >  0.50
|   |   |   |   |   |   |   |   |--- weights: [5.96, 0.00] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  153.15
|   |   |   |   |   |   |   |--- weights: [12.67, 3.04] class: 0.0
|   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |--- weights: [67.10, 0.00] class: 0.0
|--- lead_time >  151.50
|   |--- avg_price_per_room <= 100.04
|   |   |--- no_of_special_requests <= 0.50
|   |   |   |--- no_of_adults <= 1.50
|   |   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |   |--- lead_time <= 163.50
|   |   |   |   |   |   |--- lead_time <= 160.50
|   |   |   |   |   |   |   |--- weights: [2.98, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  160.50
|   |   |   |   |   |   |   |--- weights: [0.75, 24.29] class: 1.0
|   |   |   |   |   |--- lead_time >  163.50
|   |   |   |   |   |   |--- no_of_week_nights <= 4.50
|   |   |   |   |   |   |   |--- lead_time <= 173.00
|   |   |   |   |   |   |   |   |--- arrival_date <= 3.50
|   |   |   |   |   |   |   |   |   |--- weights: [46.97, 9.11] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_date >  3.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 13.66] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  173.00
|   |   |   |   |   |   |   |   |--- arrival_month <= 5.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 88.00
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 3.04] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [6.71, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  88.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 4.55] class: 1.0
|   |   |   |   |   |   |   |   |--- arrival_month >  5.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 278.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [143.15, 4.55] class: 0.0
|   |   |   |   |   |   |   |   |   |--- lead_time >  278.00
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 83.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [20.13, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  83.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |--- no_of_week_nights >  4.50
|   |   |   |   |   |   |   |--- weights: [2.24, 12.14] class: 1.0
|   |   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |   |--- avg_price_per_room <= 35.22
|   |   |   |   |   |   |--- lead_time <= 285.50
|   |   |   |   |   |   |   |--- weights: [8.20, 0.00] class: 0.0
|   |   |   |   |   |   |--- lead_time >  285.50
|   |   |   |   |   |   |   |--- weights: [0.75, 4.55] class: 1.0
|   |   |   |   |   |--- avg_price_per_room >  35.22
|   |   |   |   |   |   |--- weights: [0.75, 95.64] class: 1.0
|   |   |   |--- no_of_adults >  1.50
|   |   |   |   |--- avg_price_per_room <= 82.47
|   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |--- weights: [2.98, 282.37] class: 1.0
|   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |--- lead_time <= 244.00
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 1.50
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 166.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  166.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 57.69] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  1.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [17.89, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- arrival_month <= 9.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 3.04] class: 0.0
|   |   |   |   |   |   |   |   |   |   |--- arrival_month >  9.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 12.14] class: 1.0
|   |   |   |   |   |   |   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [75.30, 12.14] class: 0.0
|   |   |   |   |   |   |   |--- lead_time >  244.00
|   |   |   |   |   |   |   |   |--- arrival_year <= 2017.50
|   |   |   |   |   |   |   |   |   |--- weights: [25.35, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- arrival_year >  2017.50
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room <= 80.38
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights <= 3.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [11.18, 264.15] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- no_of_week_nights >  3.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- avg_price_per_room >  80.38
|   |   |   |   |   |   |   |   |   |   |--- weights: [7.46, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |--- weights: [46.22, 0.00] class: 0.0
|   |   |   |   |--- avg_price_per_room >  82.47
|   |   |   |   |   |--- no_of_adults <= 2.50
|   |   |   |   |   |   |--- type_of_meal_plan <= 1.50
|   |   |   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 <= 0.50
|   |   |   |   |   |   |   |   |   |--- weights: [8.95, 982.22] class: 1.0
|   |   |   |   |   |   |   |   |--- room_type_reserved_Room_Type 4 >  0.50
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 10.63] class: 1.0
|   |   |   |   |   |   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |   |   |   |   |   |--- weights: [4.47, 0.00] class: 0.0
|   |   |   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |   |   |   |   |   |--- weights: [5.22, 0.00] class: 0.0
|   |   |   |   |   |   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |   |   |   |   |   |--- weights: [0.00, 21.25] class: 1.0
|   |   |   |   |   |   |--- type_of_meal_plan >  1.50
|   |   |   |   |   |   |   |--- lead_time <= 249.75
|   |   |   |   |   |   |   |   |--- weights: [0.00, 16.70] class: 1.0
|   |   |   |   |   |   |   |--- lead_time >  249.75
|   |   |   |   |   |   |   |   |--- weights: [5.22, 0.00] class: 0.0
|   |   |   |   |   |--- no_of_adults >  2.50
|   |   |   |   |   |   |--- weights: [5.22, 0.00] class: 0.0
|   |   |--- no_of_special_requests >  0.50
|   |   |   |--- no_of_weekend_nights <= 0.50
|   |   |   |   |--- lead_time <= 180.50
|   |   |   |   |   |--- lead_time <= 159.50
|   |   |   |   |   |   |--- arrival_month <= 8.50
|   |   |   |   |   |   |   |--- weights: [5.96, 0.00] class: 0.0
|   |   |   |   |   |   |--- arrival_month >  8.50
|   |   |   |   |   |   |   |--- weights: [1.49, 7.59] class: 1.0
|   |   |   |   |   |--- lead_time >  159.50
|   |   |   |   |   |   |--- arrival_date <= 1.50
|   |   |   |   |   |   |   |--- weights: [1.49, 3.04] class: 1.0
|   |   |   |   |   |   |--- arrival_date >  1.50
|   |   |   |   |   |   |   |--- weights: [35.79, 1.52] class: 0.0
|   |   |   |   |--- lead_time >  180.50
|   |   |   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |   |   |--- market_segment_type_Online <= 0.50
|   |   |   |   |   |   |   |--- no_of_adults <= 2.50
|   |   |   |   |   |   |   |   |--- weights: [12.67, 3.04] class: 0.0
|   |   |   |   |   |   |   |--- no_of_adults >  2.50
|   |   |   |   |   |   |   |   |--- weights: [0.00, 3.04] class: 1.0
|   |   |   |   |   |   |--- market_segment_type_Online >  0.50
|   |   |   |   |   |   |   |--- weights: [7.46, 206.46] class: 1.0
|   |   |   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |   |   |--- weights: [8.95, 0.00] class: 0.0
|   |   |   |--- no_of_weekend_nights >  0.50
|   |   |   |   |--- market_segment_type_Offline <= 0.50
|   |   |   |   |   |--- arrival_month <= 11.50
|   |   |   |   |   |   |--- avg_price_per_room <= 76.48
|   |   |   |   |   |   |   |--- weights: [46.97, 4.55] class: 0.0
|   |   |   |   |   |   |--- avg_price_per_room >  76.48
|   |   |   |   |   |   |   |--- arrival_date <= 27.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 5.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 233.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 152.50
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [1.49, 4.55] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  152.50
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
|   |   |   |   |   |   |   |   |   |--- lead_time >  233.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [23.11, 19.74] class: 0.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  5.50
|   |   |   |   |   |   |   |   |   |--- weights: [8.95, 16.70] class: 1.0
|   |   |   |   |   |   |   |--- arrival_date >  27.50
|   |   |   |   |   |   |   |   |--- no_of_week_nights <= 1.50
|   |   |   |   |   |   |   |   |   |--- weights: [2.24, 15.18] class: 1.0
|   |   |   |   |   |   |   |   |--- no_of_week_nights >  1.50
|   |   |   |   |   |   |   |   |   |--- lead_time <= 269.00
|   |   |   |   |   |   |   |   |   |   |--- lead_time <= 176.00
|   |   |   |   |   |   |   |   |   |   |   |--- weights: [2.24, 7.59] class: 1.0
|   |   |   |   |   |   |   |   |   |   |--- lead_time >  176.00
|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
|   |   |   |   |   |   |   |   |   |--- lead_time >  269.00
|   |   |   |   |   |   |   |   |   |   |--- weights: [0.00, 4.55] class: 1.0
|   |   |   |   |   |--- arrival_month >  11.50
|   |   |   |   |   |   |--- arrival_date <= 14.50
|   |   |   |   |   |   |   |--- weights: [8.20, 3.04] class: 0.0
|   |   |   |   |   |   |--- arrival_date >  14.50
|   |   |   |   |   |   |   |--- weights: [11.18, 31.88] class: 1.0
|   |   |   |   |--- market_segment_type_Offline >  0.50
|   |   |   |   |   |--- weights: [112.58, 7.59] class: 0.0
|   |--- avg_price_per_room >  100.04
|   |   |--- arrival_month <= 11.50
|   |   |   |--- no_of_special_requests <= 2.50
|   |   |   |   |--- weights: [0.00, 3200.19] class: 1.0
|   |   |   |--- no_of_special_requests >  2.50
|   |   |   |   |--- weights: [23.11, 0.00] class: 0.0
|   |   |--- arrival_month >  11.50
|   |   |   |--- no_of_special_requests <= 0.50
|   |   |   |   |--- weights: [35.04, 0.00] class: 0.0
|   |   |   |--- no_of_special_requests >  0.50
|   |   |   |   |--- arrival_date <= 24.50
|   |   |   |   |   |--- weights: [3.73, 0.00] class: 0.0
|   |   |   |   |--- arrival_date >  24.50
|   |   |   |   |   |--- weights: [3.73, 22.77] class: 1.0


importances = best_model.feature_importances_
indices = np.argsort(importances)

plt.figure(figsize=(12, 12))
plt.title("Feature Importances")
plt.barh(range(len(indices)), importances[indices], color="violet", align="center")
plt.yticks(range(len(indices)), [feature_names[i] for i in indices])
plt.xlabel("Relative Importance")
plt.show()


# training performance comparison

models_train_comp_df = pd.concat(
    [
        decision_tree_perf_train.T,
        decision_tree_tune_perf_train.T,
        decision_tree_post_perf_train.T,
    ],
    axis=1,
)
models_train_comp_df.columns = [
    "Decision Tree sklearn",
    "Decision Tree (Pre-Pruning)",
    "Decision Tree (Post-Pruning)",
]
print("Training performance comparison:")
models_train_comp_df

Training performance comparison:


# testing performance comparison

models_test_comp_df = pd.concat(
    [
        decision_tree_perf_test.T,
        decision_tree_tune_perf_test.T,
        decision_tree_post_perf_test.T,
    ],
    axis=1,
)
models_test_comp_df.columns = [
    "Decision Tree sklearn",
    "Decision Tree (Pre-Pruning)",
    "Decision Tree (Post-Pruning)",
]
print("Testing performance comparison:")
models_test_comp_df

Testing performance comparison:

	count	unique	top	freq	mean	std	min	25%	50%	75%	max
Booking_ID	36275	36275	INN04089	1	NaN	NaN	NaN	NaN	NaN	NaN	NaN
no_of_adults	36275.0	NaN	NaN	NaN	1.844962	0.518715	0.0	2.0	2.0	2.0	4.0
no_of_children	36275.0	NaN	NaN	NaN	0.105279	0.402648	0.0	0.0	0.0	0.0	10.0
no_of_weekend_nights	36275.0	NaN	NaN	NaN	0.810724	0.870644	0.0	0.0	1.0	2.0	7.0
no_of_week_nights	36275.0	NaN	NaN	NaN	2.2043	1.410905	0.0	1.0	2.0	3.0	17.0
type_of_meal_plan	36275	4	Meal Plan 1	27835	NaN	NaN	NaN	NaN	NaN	NaN	NaN
required_car_parking_space	36275.0	NaN	NaN	NaN	0.030986	0.173281	0.0	0.0	0.0	0.0	1.0
room_type_reserved	36275	7	Room_Type 1	28130	NaN	NaN	NaN	NaN	NaN	NaN	NaN
lead_time	36275.0	NaN	NaN	NaN	85.232557	85.930817	0.0	17.0	57.0	126.0	443.0
arrival_year	36275.0	NaN	NaN	NaN	2017.820427	0.383836	2017.0	2018.0	2018.0	2018.0	2018.0
arrival_month	36275.0	NaN	NaN	NaN	7.423653	3.069894	1.0	5.0	8.0	10.0	12.0
arrival_date	36275.0	NaN	NaN	NaN	15.596995	8.740447	1.0	8.0	16.0	23.0	31.0
market_segment_type	36275	5	Online	23214	NaN	NaN	NaN	NaN	NaN	NaN	NaN
repeated_guest	36275.0	NaN	NaN	NaN	0.025637	0.158053	0.0	0.0	0.0	0.0	1.0
no_of_previous_cancellations	36275.0	NaN	NaN	NaN	0.023349	0.368331	0.0	0.0	0.0	0.0	13.0
no_of_previous_bookings_not_canceled	36275.0	NaN	NaN	NaN	0.153411	1.754171	0.0	0.0	0.0	0.0	58.0
avg_price_per_room	36275.0	NaN	NaN	NaN	103.423539	35.089424	0.0	80.3	99.45	120.0	540.0
no_of_special_requests	36275.0	NaN	NaN	NaN	0.619655	0.786236	0.0	0.0	0.0	1.0	5.0
booking_status	36275	2	Not_Canceled	24390	NaN	NaN	NaN	NaN	NaN	NaN	NaN

	const	no_of_adults	no_of_weekend_nights	no_of_week_nights	type_of_meal_plan	required_car_parking_space	lead_time	arrival_year	arrival_month	arrival_date	repeated_guest	no_of_previous_cancellations	avg_price_per_room	no_of_special_requests
Odds	0.0	1.089464	1.226745	1.032097	0.694660	0.245988	1.014492	1.811065	0.951089	1.004270	0.079137	1.266534	1.023714	0.308737
Change_odd%	-100.0	8.946383	22.674519	3.209689	-30.534044	-75.401164	1.449175	81.106544	-4.891070	0.426974	-92.086280	26.653447	2.371355	-69.126284

	Logistic Regression-default Threshold (0.5)	Logistic Regression-0.31 Threshold	Logistic Regression-0.42 Threshold
Accuracy	0.787138	0.766186	0.781191
Recall	0.577473	0.769564	0.660777
Precision	0.717658	0.614277	0.667841
F1	0.639979	0.683208	0.664290

	Logistic Regression-default Threshold (0.5)	Logistic Regression-0.31 Threshold	Logistic Regression-0.42 Threshold
Accuracy	0.787138	0.766186	0.781191
Recall	0.577473	0.769564	0.660777
Precision	0.717658	0.614277	0.667841
F1	0.639979	0.683208	0.664290

	Logistic Regression-default Threshold (0.5)	Logistic Regression-0.31 Threshold	Logistic Regression-0.42 Threshold
Accuracy	0.784067	0.759809	0.776165
Recall	0.574313	0.763881	0.654515
Precision	0.711111	0.605872	0.659695
F1	0.635433	0.675763	0.657095

	Booking_ID	no_of_adults	no_of_children	no_of_weekend_nights	no_of_week_nights	type_of_meal_plan	room_type_reserved	lead_time	arrival_year	arrival_month	arrival_date	market_segment_type	avg_price_per_room	no_of_special_requests	booking_status
17949	INN17950	1	0	2	1	Meal Plan 2	Room_Type 1	122	2018	3	27	Offline	86.00	1	Not_Canceled
11766	INN11767	2	0	1	1	Meal Plan 1	Room_Type 1	60	2017	10	12	Offline	65.00	1	Not_Canceled
32026	INN32027	2	0	1	0	Meal Plan 1	Room_Type 1	11	2017	8	24	Online	90.00	1	Not_Canceled
26671	INN26672	2	0	0	4	Meal Plan 1	Room_Type 1	270	2018	4	20	Offline	62.80	0	Canceled
21857	INN21858	2	0	2	2	Meal Plan 1	Room_Type 1	219	2018	10	22	Online	90.95	2	Not_Canceled
30740	INN30741	2	0	2	3	Meal Plan 1	Room_Type 4	26	2017	10	4	Online	79.85	1	Canceled
23706	INN23707	2	0	2	3	Not Selected	Room_Type 1	61	2018	7	23	Online	94.50	1	Not_Canceled
13197	INN13198	2	0	0	2	Meal Plan 1	Room_Type 1	245	2018	6	17	Offline	75.00	0	Canceled
14078	INN14079	3	0	0	3	Meal Plan 1	Room_Type 4	120	2018	6	2	Online	159.30	1	Canceled
7827	INN07828	2	0	2	1	Meal Plan 1	Room_Type 1	88	2018	12	18	Offline	75.00	0	Not_Canceled
34632	INN34633	2	0	1	3	Not Selected	Room_Type 1	26	2018	10	3	Online	103.76	1	Not_Canceled
11748	INN11749	3	0	1	4	Meal Plan 2	Room_Type 1	197	2018	12	21	Offline	160.60	0	Not_Canceled
34636	INN34637	1	0	0	2	Meal Plan 1	Room_Type 1	4	2018	6	24	Offline	95.00	0	Not_Canceled
14320	INN14321	2	1	0	3	Meal Plan 1	Room_Type 1	51	2018	12	6	Online	109.80	2	Not_Canceled
3183	INN03184	2	0	1	2	Meal Plan 1	Room_Type 1	34	2017	10	12	Online	103.50	1	Not_Canceled

	Booking_ID	no_of_adults	no_of_children	no_of_weekend_nights	no_of_week_nights	type_of_meal_plan	required_car_parking_space	room_type_reserved	lead_time	arrival_year	arrival_month	arrival_date	market_segment_type	repeated_guest	no_of_previous_cancellations	no_of_previous_bookings_not_canceled	avg_price_per_room	no_of_special_requests	booking_status
32	INN00033	0	2	0	3	Meal Plan 1	0	Room_Type 2	56	2018	12	7	Online	0	0	0	82.44	1	Not_Canceled
287	INN00288	0	2	2	2	Meal Plan 1	0	Room_Type 1	68	2018	4	24	Online	0	0	0	108.38	1	Canceled
653	INN00654	0	2	1	2	Meal Plan 1	0	Room_Type 2	78	2018	8	19	Online	0	0	0	115.68	1	Not_Canceled
937	INN00938	0	2	0	3	Meal Plan 1	0	Room_Type 2	40	2018	1	14	Online	0	0	0	6.67	1	Not_Canceled
954	INN00955	0	2	1	1	Meal Plan 1	0	Room_Type 2	92	2018	10	29	Online	0	0	0	81.50	2	Not_Canceled
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
34720	INN34721	0	2	0	3	Meal Plan 1	0	Room_Type 2	76	2018	9	21	Online	0	0	0	127.38	3	Not_Canceled
34730	INN34731	0	2	1	1	Meal Plan 1	0	Room_Type 2	178	2018	8	27	Online	0	0	0	88.77	0	Canceled
34890	INN34891	0	2	2	2	Meal Plan 1	0	Room_Type 2	31	2018	9	16	Online	0	0	0	124.25	2	Not_Canceled
35691	INN35692	0	2	2	1	Meal Plan 1	0	Room_Type 2	75	2018	3	19	Online	0	0	0	78.00	0	Canceled
35797	INN35798	0	2	0	2	Meal Plan 1	0	Room_Type 2	120	2018	6	30	Online	0	0	0	97.55	0	Not_Canceled

	no_of_adults	no_of_weekend_nights	no_of_week_nights	type_of_meal_plan	room_type_reserved	lead_time	arrival_year	arrival_month	arrival_date	market_segment_type	avg_price_per_room	no_of_special_requests	booking_status
31254	2	2	3	Meal Plan 1	Room_Type 1	10	2018	12	3	Online	89.59	0	Not_Canceled
3317	2	0	3	Not Selected	Room_Type 1	37	2018	12	8	Online	88.00	0	Canceled
4843	2	1	2	Meal Plan 1	Room_Type 1	25	2018	10	17	Offline	85.00	0	Not_Canceled
13529	2	0	2	Meal Plan 1	Room_Type 1	16	2017	9	9	Online	105.00	2	Not_Canceled
33793	2	2	3	Not Selected	Room_Type 1	200	2018	12	1	Offline	51.00	0	Not_Canceled

	ccp_alphas	impurities
0	0.000000e+00	0.008376
1	0.000000e+00	0.008376
2	1.303920e-20	0.008376
3	1.303920e-20	0.008376
4	1.303920e-20	0.008376
...	...	...
1904	8.901596e-03	0.328058
1905	9.802243e-03	0.337860
1906	1.271875e-02	0.350579
1907	3.412090e-02	0.418821
1908	8.117914e-02	0.500000

	Decision Tree sklearn	Decision Tree (Pre-Pruning)	Decision Tree (Post-Pruning)
Accuracy	0.994211	0.879923	0.896542
Recall	0.986608	0.856989	0.902786
Precision	0.995776	0.794568	0.806279
F1	0.991171	0.824599	0.851808

	Decision Tree sklearn	Decision Tree (Pre-Pruning)	Decision Tree (Post-Pruning)
Accuracy	0.872278	0.869981	0.866948
Recall	0.808348	0.839012	0.857751
Precision	0.799270	0.777018	0.761341
F1	0.803783	0.806826	0.806676

INN Hotels Project¶

Context¶

Objective¶

Data Description¶

1- Importing necessary libraries and data¶

2- Data Overview¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

3- Exploratory Data Analysis (EDA)¶

3-1 Univariate Analysis¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

3-2 Bivariate Analysis¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

Observation¶

4- Data Preprocessing¶

4-1 Missing value treatment¶

Observation¶

4-2 Feature engineering¶

4-3 Outlier detection and treatment¶

5- EDA¶

Observation¶

6- Data Preparation for modeling¶

6-1 Splitting data into train and test¶

6-2 Check model parameters and performance¶

7- Building a Logistic Regression model¶

7-1 Model evaluation criterion¶

Model can make wrong predictions as:¶

Which case is more important?¶

How to reduce the losses?¶

First, let's create functions to calculate different metrics and confusion matrix so that we don't have to use the same code repeatedly for each model.¶

7-2 Logistic Regression (with statsmodels library)¶

Checking model performance¶

7-3 Checking Multicollinearity¶

7-4 Converting coefficients to odds¶

Coefficient interpretations¶

7-5 Model performance evaluation¶

ROC-AUC¶

7-6 Model Performance Improvement¶

Optimal threshold using AUC-ROC curve¶

Checking model performance on training set¶

Let's use Precision-Recall curve and see if we can find a better threshold¶

7-7 Final Model Summary¶

Model Performance Summary¶

Let's check the performance on the test set¶

Using model with default threshold¶

ROC curve on test set¶

Model performance summary¶

Conclusion¶

8- Building a Decision Tree model¶

8-1 Build the model¶

Checking model performance on training set¶

Checking model performance on testing set¶